{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1数据加载\n",
    "# 2数据探索与预处理\n",
    "## 2.1数据特征探索\n",
    "## 2.2按照时间聚合目标值total_purchase_amt和total_redeem_amt\n",
    "## 2.3目标值可视化\n",
    "## 2.4准备目标值\n",
    "# 3ARIMA预测\n",
    "## 3.1数据的平稳性 ADF检测\n",
    "## 3.2一阶差分及平稳性检测\n",
    "## 3.3模型训练与预测\n",
    "## 3.4预测结果可视化\n",
    "## 3.5结果输出与提交"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['axes.unicode_minus'] = False#这句代码解决待会画图出来  坐标轴负号乱码问题"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1数据加载"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "         user_id  report_date  tBalance  yBalance  total_purchase_amt  \\\n",
       "0              1     20140805     20385     20383                   2   \n",
       "1              1     20140808     20391     20389                   2   \n",
       "2              1     20140811     20397     20395                   2   \n",
       "3              1     20140814     20403     20401                   2   \n",
       "4              1     20140817     20409     20407                   2   \n",
       "...          ...          ...       ...       ...                 ...   \n",
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       "\n",
       "         direct_purchase_amt  purchase_bal_amt  purchase_bank_amt  \\\n",
       "0                          0                 0                  0   \n",
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       "2                          0                 0                  0   \n",
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       "...                      ...               ...                ...   \n",
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       "\n",
       "         total_redeem_amt  consume_amt  transfer_amt  tftobal_amt  \\\n",
       "0                       0            0             0            0   \n",
       "1                       0            0             0            0   \n",
       "2                       0            0             0            0   \n",
       "3                       0            0             0            0   \n",
       "4                       0            0             0            0   \n",
       "...                   ...          ...           ...          ...   \n",
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       "2840418                 0            0             0            0   \n",
       "2840419             31732            0         31732            0   \n",
       "2840420                 0            0             0            0   \n",
       "\n",
       "         tftocard_amt  share_amt  category1  category2  category3  category4  \n",
       "0                   0          2        NaN        NaN        NaN        NaN  \n",
       "1                   0          2        NaN        NaN        NaN        NaN  \n",
       "2                   0          2        NaN        NaN        NaN        NaN  \n",
       "3                   0          2        NaN        NaN        NaN        NaN  \n",
       "4                   0          2        NaN        NaN        NaN        NaN  \n",
       "...               ...        ...        ...        ...        ...        ...  \n",
       "2840416             0         61        NaN        NaN        NaN        NaN  \n",
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       "2840419         31732       2298        NaN        NaN        NaN        NaN  \n",
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       "\n",
       "[2840421 rows x 18 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据加载\n",
    "data=pd.read_csv('user_balance_table.csv')\n",
    "data#数据是读取进来了  但是里面有日期的格式 需要将日期格式读取进来 就是report_date那一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
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       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840417</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-08-31</td>\n",
       "      <td>525707</td>\n",
       "      <td>538147</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12500</td>\n",
       "      <td>12500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>60</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840418</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-07-24</td>\n",
       "      <td>20487121</td>\n",
       "      <td>20484824</td>\n",
       "      <td>2297</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2297</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840419</th>\n",
       "      <td>28033</td>\n",
       "      <td>2014-07-27</td>\n",
       "      <td>20462288</td>\n",
       "      <td>20491722</td>\n",
       "      <td>2298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>0</td>\n",
       "      <td>31732</td>\n",
       "      <td>2298</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2840420</th>\n",
       "      <td>28035</td>\n",
       "      <td>2014-03-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2840421 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id report_date  tBalance  yBalance  total_purchase_amt  \\\n",
       "0              1  2014-08-05     20385     20383                   2   \n",
       "1              1  2014-08-08     20391     20389                   2   \n",
       "2              1  2014-08-11     20397     20395                   2   \n",
       "3              1  2014-08-14     20403     20401                   2   \n",
       "4              1  2014-08-17     20409     20407                   2   \n",
       "...          ...         ...       ...       ...                 ...   \n",
       "2840416    28033  2014-08-25    550646    550585                  61   \n",
       "2840417    28033  2014-08-31    525707    538147                  60   \n",
       "2840418    28033  2014-07-24  20487121  20484824                2297   \n",
       "2840419    28033  2014-07-27  20462288  20491722                2298   \n",
       "2840420    28035  2014-03-05         0         0                   0   \n",
       "\n",
       "         direct_purchase_amt  purchase_bal_amt  purchase_bank_amt  \\\n",
       "0                          0                 0                  0   \n",
       "1                          0                 0                  0   \n",
       "2                          0                 0                  0   \n",
       "3                          0                 0                  0   \n",
       "4                          0                 0                  0   \n",
       "...                      ...               ...                ...   \n",
       "2840416                    0                 0                  0   \n",
       "2840417                    0                 0                  0   \n",
       "2840418                    0                 0                  0   \n",
       "2840419                    0                 0                  0   \n",
       "2840420                    0                 0                  0   \n",
       "\n",
       "         total_redeem_amt  consume_amt  transfer_amt  tftobal_amt  \\\n",
       "0                       0            0             0            0   \n",
       "1                       0            0             0            0   \n",
       "2                       0            0             0            0   \n",
       "3                       0            0             0            0   \n",
       "4                       0            0             0            0   \n",
       "...                   ...          ...           ...          ...   \n",
       "2840416                 0            0             0            0   \n",
       "2840417             12500        12500             0            0   \n",
       "2840418                 0            0             0            0   \n",
       "2840419             31732            0         31732            0   \n",
       "2840420                 0            0             0            0   \n",
       "\n",
       "         tftocard_amt  share_amt  category1  category2  category3  category4  \n",
       "0                   0          2        NaN        NaN        NaN        NaN  \n",
       "1                   0          2        NaN        NaN        NaN        NaN  \n",
       "2                   0          2        NaN        NaN        NaN        NaN  \n",
       "3                   0          2        NaN        NaN        NaN        NaN  \n",
       "4                   0          2        NaN        NaN        NaN        NaN  \n",
       "...               ...        ...        ...        ...        ...        ...  \n",
       "2840416             0         61        NaN        NaN        NaN        NaN  \n",
       "2840417             0         60        0.0        0.0        0.0    12500.0  \n",
       "2840418             0       2297        NaN        NaN        NaN        NaN  \n",
       "2840419         31732       2298        NaN        NaN        NaN        NaN  \n",
       "2840420             0          0        NaN        NaN        NaN        NaN  \n",
       "\n",
       "[2840421 rows x 18 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_csv('user_balance_table.csv',parse_dates=['report_date'])\n",
    "data#user_id就是用户 report_date是日期 tBalance是今日余额  yBalance是昨日余额  total_purchase_amt 今日总购买量（=直接购买+收益）\n",
    "#direct_purchase_amt是直接购买  purchase_bal_amt今日支付宝余额购买量  purchase_bank_amt今日银行卡购买量 \n",
    "#total_redeem_amt今日总赎回量（=消费+转出） consume_amt今日总消费量 transfer_amt今日转出总量   \n",
    "#tftobal_amt今日转出到支付宝余额总量 tftocard_amt今日转出到银行卡总量   share_amt今日收益\n",
    "#category1 category2 category3 category4分别表示类目1 2 3 4 消费总额\n",
    "#其中 total_purchase_amt 和 total_redeem_amt 是我们要预测的目标值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2数据探索与预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.1数据特征探索"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-07-01      441\n",
       "2013-07-02      480\n",
       "2013-07-03      499\n",
       "2013-07-04      523\n",
       "2013-07-05      544\n",
       "              ...  \n",
       "2014-08-27    12527\n",
       "2014-08-28    12557\n",
       "2014-08-29    12596\n",
       "2014-08-30    12603\n",
       "2014-08-31    12614\n",
       "Name: report_date, Length: 427, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['report_date'].value_counts().sort_index()#2840421个数据里面 时间只有427个  时间最早是从2013-07-01  最晚是到2018-31-31"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2840421 entries, 0 to 2840420\n",
      "Data columns (total 18 columns):\n",
      " #   Column               Dtype         \n",
      "---  ------               -----         \n",
      " 0   user_id              int64         \n",
      " 1   report_date          datetime64[ns]\n",
      " 2   tBalance             int64         \n",
      " 3   yBalance             int64         \n",
      " 4   total_purchase_amt   int64         \n",
      " 5   direct_purchase_amt  int64         \n",
      " 6   purchase_bal_amt     int64         \n",
      " 7   purchase_bank_amt    int64         \n",
      " 8   total_redeem_amt     int64         \n",
      " 9   consume_amt          int64         \n",
      " 10  transfer_amt         int64         \n",
      " 11  tftobal_amt          int64         \n",
      " 12  tftocard_amt         int64         \n",
      " 13  share_amt            int64         \n",
      " 14  category1            float64       \n",
      " 15  category2            float64       \n",
      " 16  category3            float64       \n",
      " 17  category4            float64       \n",
      "dtypes: datetime64[ns](1), float64(4), int64(13)\n",
      "memory usage: 390.1 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()# 'report_date'这个字段的类型是datetime64[ns]  其他的都是整形和浮点型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.2按照时间聚合目标值total_purchase_amt和total_redeem_amt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>32488348</td>\n",
       "      <td>5525022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>29037390</td>\n",
       "      <td>2554548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>27270770</td>\n",
       "      <td>5953867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>18321185</td>\n",
       "      <td>6410729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>11648749</td>\n",
       "      <td>2763587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>302194801</td>\n",
       "      <td>468164147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>245082751</td>\n",
       "      <td>297893861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>267554713</td>\n",
       "      <td>273756380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>199708772</td>\n",
       "      <td>196374134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>275090213</td>\n",
       "      <td>292943033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt  total_redeem_amt\n",
       "report_date                                      \n",
       "2013-07-01             32488348           5525022\n",
       "2013-07-02             29037390           2554548\n",
       "2013-07-03             27270770           5953867\n",
       "2013-07-04             18321185           6410729\n",
       "2013-07-05             11648749           2763587\n",
       "...                         ...               ...\n",
       "2014-08-27            302194801         468164147\n",
       "2014-08-28            245082751         297893861\n",
       "2014-08-29            267554713         273756380\n",
       "2014-08-30            199708772         196374134\n",
       "2014-08-31            275090213         292943033\n",
       "\n",
       "[427 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#这个时候可以根据时间来做一个分组聚合操作\n",
    "total_balance=data.groupby(['report_date'])['total_purchase_amt','total_redeem_amt'].sum()\n",
    "total_balance#这里果然是427行  然后对应的天数 total_purchase_amt求和了  total_redeem_amt也求和了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>32488348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>29037390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>27270770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>18321185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>11648749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>302194801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>245082751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>267554713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>199708772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>275090213</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt\n",
       "report_date                    \n",
       "2013-07-01             32488348\n",
       "2013-07-02             29037390\n",
       "2013-07-03             27270770\n",
       "2013-07-04             18321185\n",
       "2013-07-05             11648749\n",
       "...                         ...\n",
       "2014-08-27            302194801\n",
       "2014-08-28            245082751\n",
       "2014-08-29            267554713\n",
       "2014-08-30            199708772\n",
       "2014-08-31            275090213\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purchase=total_balance[['total_purchase_amt']]\n",
    "purchase#这样就有了一个新的dataframe 专门存储 某天的购买  这个也是我们要预测的这一列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>5525022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>2554548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>5953867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>6410729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>2763587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>468164147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>297893861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>273756380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>196374134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>292943033</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_redeem_amt\n",
       "report_date                  \n",
       "2013-07-01            5525022\n",
       "2013-07-02            2554548\n",
       "2013-07-03            5953867\n",
       "2013-07-04            6410729\n",
       "2013-07-05            2763587\n",
       "...                       ...\n",
       "2014-08-27          468164147\n",
       "2014-08-28          297893861\n",
       "2014-08-29          273756380\n",
       "2014-08-30          196374134\n",
       "2014-08-31          292943033\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "redeem=total_balance[['total_redeem_amt']]\n",
    "redeem#这个dataframe专门存储赎回 也就是当天的赎回（消费+转出）  这个也是我们要预测的一列"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.3目标值可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "#指定区间范围内的数据,进行可视化\n",
    "def plot_stl(data):\n",
    "    #STL返回三个部分：trend(趋势),seasonal(季节),residual(残差)\n",
    "    result=sm.tsa.seasonal_decompose(data,period=30)#我们的数据量只有从2013-07-01到2014-08-31一年多的数据量 而且我们要预测的仅仅是下一个月\n",
    "    #所以这里的参数period=30 算是一个周期      如果像股票那样周期是年的  可以设置成200\n",
    "    #可视化\n",
    "    fig=plt.figure(figsize=(12,8))\n",
    "    ax1=fig.add_subplot(311)\n",
    "    ax2=fig.add_subplot(312)\n",
    "    ax3=fig.add_subplot(313)\n",
    "    #result里面包含三个部分 trend(趋势),seasonal(季节),residual(残差)\n",
    "    result.trend.plot(ax=ax1,title='Trend趋势')\n",
    "    result.seasonal.plot(ax=ax2,title='Seasonal季节')\n",
    "    result.resid.plot(ax=ax3,title='Resid残差')\n",
    "plot_stl(purchase['total_purchase_amt'])#这里三张图的横坐标都是表格中的日期类型  从2013年7月到2014年8月"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_stl(redeem['total_redeem_amt'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-04-01</th>\n",
       "      <td>453320585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-02</th>\n",
       "      <td>355347118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-03</th>\n",
       "      <td>363877120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-04</th>\n",
       "      <td>251895894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-05</th>\n",
       "      <td>202336542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-06</th>\n",
       "      <td>129477254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-07</th>\n",
       "      <td>196936223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-08</th>\n",
       "      <td>354770149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-09</th>\n",
       "      <td>383347565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-10</th>\n",
       "      <td>386567460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-11</th>\n",
       "      <td>237829882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-12</th>\n",
       "      <td>177642053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-13</th>\n",
       "      <td>208172985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-14</th>\n",
       "      <td>309853269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-15</th>\n",
       "      <td>428681231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-16</th>\n",
       "      <td>387847838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-17</th>\n",
       "      <td>355792647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-18</th>\n",
       "      <td>239300383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-19</th>\n",
       "      <td>268729366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-20</th>\n",
       "      <td>191259529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-21</th>\n",
       "      <td>301134667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-22</th>\n",
       "      <td>285248757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-23</th>\n",
       "      <td>313677307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-24</th>\n",
       "      <td>318358891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-25</th>\n",
       "      <td>220927432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-26</th>\n",
       "      <td>151625415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-27</th>\n",
       "      <td>146837951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-28</th>\n",
       "      <td>324937272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-29</th>\n",
       "      <td>330607104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-30</th>\n",
       "      <td>260091330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-01</th>\n",
       "      <td>193045106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-02</th>\n",
       "      <td>125336258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-03</th>\n",
       "      <td>185094488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-04</th>\n",
       "      <td>303087562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-05</th>\n",
       "      <td>370924149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-06</th>\n",
       "      <td>318002728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-07</th>\n",
       "      <td>417327518</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt\n",
       "report_date                    \n",
       "2014-04-01            453320585\n",
       "2014-04-02            355347118\n",
       "2014-04-03            363877120\n",
       "2014-04-04            251895894\n",
       "2014-04-05            202336542\n",
       "2014-04-06            129477254\n",
       "2014-04-07            196936223\n",
       "2014-04-08            354770149\n",
       "2014-04-09            383347565\n",
       "2014-04-10            386567460\n",
       "2014-04-11            237829882\n",
       "2014-04-12            177642053\n",
       "2014-04-13            208172985\n",
       "2014-04-14            309853269\n",
       "2014-04-15            428681231\n",
       "2014-04-16            387847838\n",
       "2014-04-17            355792647\n",
       "2014-04-18            239300383\n",
       "2014-04-19            268729366\n",
       "2014-04-20            191259529\n",
       "2014-04-21            301134667\n",
       "2014-04-22            285248757\n",
       "2014-04-23            313677307\n",
       "2014-04-24            318358891\n",
       "2014-04-25            220927432\n",
       "2014-04-26            151625415\n",
       "2014-04-27            146837951\n",
       "2014-04-28            324937272\n",
       "2014-04-29            330607104\n",
       "2014-04-30            260091330\n",
       "2014-05-01            193045106\n",
       "2014-05-02            125336258\n",
       "2014-05-03            185094488\n",
       "2014-05-04            303087562\n",
       "2014-05-05            370924149\n",
       "2014-05-06            318002728\n",
       "2014-05-07            417327518"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#通过观察purchase的Trend发现 找一段平稳的数据进行一下观察\n",
    "purchase2=purchase[(purchase.index>='2014-04-01')&(purchase.index<='2014-05-07')]\n",
    "purchase2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3ARIMA预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1数据的平稳性 ADF检测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#然后可视化一下\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.plot(purchase2['total_purchase_amt'])\n",
    "data_range=pd.date_range('2014-04-01','2014-05-07')\n",
    "plt.xticks(data_range,rotation=90)#查了一下日历 6号 27号 属于那种节假日  所以中购买量相对较少 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014-04-01</th>\n",
       "      <td>277429358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-02</th>\n",
       "      <td>272612066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-03</th>\n",
       "      <td>266605457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-04</th>\n",
       "      <td>200192637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-05</th>\n",
       "      <td>163199682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-06</th>\n",
       "      <td>139576683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-07</th>\n",
       "      <td>176966561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-08</th>\n",
       "      <td>250015131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-09</th>\n",
       "      <td>289330278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-10</th>\n",
       "      <td>286914864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-11</th>\n",
       "      <td>277077434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-12</th>\n",
       "      <td>123295320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-13</th>\n",
       "      <td>178934722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-14</th>\n",
       "      <td>415986984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-15</th>\n",
       "      <td>285293076</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-16</th>\n",
       "      <td>255914640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-17</th>\n",
       "      <td>265341592</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-18</th>\n",
       "      <td>225952909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-19</th>\n",
       "      <td>146374940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-20</th>\n",
       "      <td>161057781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-21</th>\n",
       "      <td>295635256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-22</th>\n",
       "      <td>268810141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-23</th>\n",
       "      <td>278470936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-24</th>\n",
       "      <td>224536754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-25</th>\n",
       "      <td>227764292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-26</th>\n",
       "      <td>158122962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-27</th>\n",
       "      <td>191915377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-28</th>\n",
       "      <td>327724735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-29</th>\n",
       "      <td>307578349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-04-30</th>\n",
       "      <td>281835975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-01</th>\n",
       "      <td>143362755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-02</th>\n",
       "      <td>121222064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-03</th>\n",
       "      <td>199568043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-04</th>\n",
       "      <td>413222034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-05</th>\n",
       "      <td>309330781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-06</th>\n",
       "      <td>341108696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-05-07</th>\n",
       "      <td>239372999</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_redeem_amt\n",
       "report_date                  \n",
       "2014-04-01          277429358\n",
       "2014-04-02          272612066\n",
       "2014-04-03          266605457\n",
       "2014-04-04          200192637\n",
       "2014-04-05          163199682\n",
       "2014-04-06          139576683\n",
       "2014-04-07          176966561\n",
       "2014-04-08          250015131\n",
       "2014-04-09          289330278\n",
       "2014-04-10          286914864\n",
       "2014-04-11          277077434\n",
       "2014-04-12          123295320\n",
       "2014-04-13          178934722\n",
       "2014-04-14          415986984\n",
       "2014-04-15          285293076\n",
       "2014-04-16          255914640\n",
       "2014-04-17          265341592\n",
       "2014-04-18          225952909\n",
       "2014-04-19          146374940\n",
       "2014-04-20          161057781\n",
       "2014-04-21          295635256\n",
       "2014-04-22          268810141\n",
       "2014-04-23          278470936\n",
       "2014-04-24          224536754\n",
       "2014-04-25          227764292\n",
       "2014-04-26          158122962\n",
       "2014-04-27          191915377\n",
       "2014-04-28          327724735\n",
       "2014-04-29          307578349\n",
       "2014-04-30          281835975\n",
       "2014-05-01          143362755\n",
       "2014-05-02          121222064\n",
       "2014-05-03          199568043\n",
       "2014-05-04          413222034\n",
       "2014-05-05          309330781\n",
       "2014-05-06          341108696\n",
       "2014-05-07          239372999"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "redeem2=redeem[(redeem.index>='2014-04-01')&(redeem.index<='2014-05-07')]\n",
    "redeem2#同理可以看一下 redeem总的支出量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x7f9882558c10>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882558290>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882403350>,\n",
       "  <matplotlib.axis.XTick at 0x7f98825b8c10>,\n",
       "  <matplotlib.axis.XTick at 0x7f98825b81d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882580ad0>,\n",
       "  <matplotlib.axis.XTick at 0x7f98825804d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882580690>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882962f90>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882962890>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882595e10>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882595a50>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882595050>,\n",
       "  <matplotlib.axis.XTick at 0x7f98823d78d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882663e50>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882962cd0>,\n",
       "  <matplotlib.axis.XTick at 0x7f98826633d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f98826638d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882663050>,\n",
       "  <matplotlib.axis.XTick at 0x7f988264e590>,\n",
       "  <matplotlib.axis.XTick at 0x7f988264e610>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882536050>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882536a50>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882536250>,\n",
       "  <matplotlib.axis.XTick at 0x7f988264e450>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882663a90>,\n",
       "  <matplotlib.axis.XTick at 0x7f988273aa50>,\n",
       "  <matplotlib.axis.XTick at 0x7f988273ab10>,\n",
       "  <matplotlib.axis.XTick at 0x7f988273a390>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882709f90>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882709590>,\n",
       "  <matplotlib.axis.XTick at 0x7f9882709510>,\n",
       "  <matplotlib.axis.XTick at 0x7f98826b6c50>,\n",
       "  <matplotlib.axis.XTick at 0x7f98826b6b90>,\n",
       "  <matplotlib.axis.XTick at 0x7f988273a8d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f98826b69d0>,\n",
       "  <matplotlib.axis.XTick at 0x7f98826b6550>],\n",
       " [Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, ''),\n",
       "  Text(0, 0, '')])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#然后可视化一下\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.plot(redeem2['total_redeem_amt'])\n",
    "data_range=pd.date_range('2014-04-01','2014-05-07')\n",
    "plt.xticks(data_range,rotation=90)#查了一下日历 6号 27号 属于那种节假日  所以总赎回量相对较少 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.5898802926313507,\n",
       " 0.4886749751375928,\n",
       " 18,\n",
       " 408,\n",
       " {'1%': -3.446479704252724,\n",
       "  '5%': -2.8686500930967354,\n",
       "  '10%': -2.5705574627547096},\n",
       " 15960.28197033403)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看一下数据的平稳性 ADF检测\n",
    "from statsmodels.tsa.stattools import adfuller\n",
    "t=adfuller(purchase['total_purchase_amt'])\n",
    "t#不能拒绝原假设（不平稳） 因为原来的数据确实不是很平稳的\n",
    "#这里的ADF结果为-1.58大于下下面的 -3.44 、-2.88、-2.57(1% 5% 10%拒绝原假设的统计值)     需要做一下一阶差分   不行了再二阶差分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_purchase_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>-3450958.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>-1766620.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>-8949585.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>-6672436.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>-4750288.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>-57112050.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>22471962.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>-67845941.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>75381441.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_purchase_amt\n",
       "report_date                    \n",
       "2013-07-01                  NaN\n",
       "2013-07-02           -3450958.0\n",
       "2013-07-03           -1766620.0\n",
       "2013-07-04           -8949585.0\n",
       "2013-07-05           -6672436.0\n",
       "...                         ...\n",
       "2014-08-27           -4750288.0\n",
       "2014-08-28          -57112050.0\n",
       "2014-08-29           22471962.0\n",
       "2014-08-30          -67845941.0\n",
       "2014-08-31           75381441.0\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff1=purchase.diff(1)#现在是一阶差分  第一个数据就是0了 一阶差分是 后一项减去前一项  第一项没有前一项可以减  所以这里是NaN的了\n",
    "diff1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-7.947102224652343,\n",
       " 3.198186862488185e-12,\n",
       " 18,\n",
       " 407,\n",
       " {'1%': -3.4465195891135845,\n",
       "  '5%': -2.8686676281678634,\n",
       "  '10%': -2.5705668101226085},\n",
       " 15918.844657651942)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#有了一阶差分之后 再来看看平稳性ADF检测\n",
    "t2=adfuller(diff1[1:])#这里从第一项开始 因为第0项已经是空的了  这里不从第一项开始 会报错\n",
    "t2#这个时候 -7.9是小于 下面1% 5% 10%的了  这个时候说明已经平稳了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-1.372413679828339,\n",
       " 0.5954275877949474,\n",
       " 13,\n",
       " 413,\n",
       " {'1%': -3.4462831955497135,\n",
       "  '5%': -2.8685636962704395,\n",
       "  '10%': -2.5705114078759914},\n",
       " 15816.780952766481)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#同理可以做一下 redeem 的假设\n",
    "t3=adfuller(redeem['total_redeem_amt'])\n",
    "t3#这个也是不平稳的  因为-1.37大于下面的几个值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.2一阶差分及平稳性检测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_redeem_amt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>report_date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-07-01</th>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-02</th>\n",
       "      <td>-2970474.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-03</th>\n",
       "      <td>3399319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-04</th>\n",
       "      <td>456862.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-07-05</th>\n",
       "      <td>-3647142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-27</th>\n",
       "      <td>182685584.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-28</th>\n",
       "      <td>-170270286.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-29</th>\n",
       "      <td>-24137481.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-30</th>\n",
       "      <td>-77382246.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-08-31</th>\n",
       "      <td>96568899.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_redeem_amt\n",
       "report_date                  \n",
       "2013-07-01                NaN\n",
       "2013-07-02         -2970474.0\n",
       "2013-07-03          3399319.0\n",
       "2013-07-04           456862.0\n",
       "2013-07-05         -3647142.0\n",
       "...                       ...\n",
       "2014-08-27        182685584.0\n",
       "2014-08-28       -170270286.0\n",
       "2014-08-29        -24137481.0\n",
       "2014-08-30        -77382246.0\n",
       "2014-08-31         96568899.0\n",
       "\n",
       "[427 rows x 1 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff2=redeem.diff(1)\n",
    "diff2#然后再做一下平稳性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-11.69198690696884,\n",
       " 1.6443717458497645e-21,\n",
       " 12,\n",
       " 413,\n",
       " {'1%': -3.4462831955497135,\n",
       "  '5%': -2.8685636962704395,\n",
       "  '10%': -2.5705114078759914},\n",
       " 15779.04993673871)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t4=adfuller(diff2[1:])\n",
    "t4#这个是-11.69是小于下面三个值的  所以这个时候 是平稳了"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.3模型训练与预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:162: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  % freq, ValueWarning)\n",
      "/opt/conda/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:162: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  % freq, ValueWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2014-09-01    3.310539e+08\n",
       "2014-09-02    3.318762e+08\n",
       "2014-09-03    3.338910e+08\n",
       "2014-09-04    2.983191e+08\n",
       "2014-09-05    2.407509e+08\n",
       "2014-09-06    2.266140e+08\n",
       "2014-09-07    2.435554e+08\n",
       "2014-09-08    2.970865e+08\n",
       "2014-09-09    3.321274e+08\n",
       "2014-09-10    3.265197e+08\n",
       "2014-09-11    2.916841e+08\n",
       "2014-09-12    2.392702e+08\n",
       "2014-09-13    2.253550e+08\n",
       "2014-09-14    2.475289e+08\n",
       "2014-09-15    2.950936e+08\n",
       "2014-09-16    3.345010e+08\n",
       "2014-09-17    3.280818e+08\n",
       "2014-09-18    2.927099e+08\n",
       "2014-09-19    2.448967e+08\n",
       "2014-09-20    2.275711e+08\n",
       "2014-09-21    2.530230e+08\n",
       "2014-09-22    2.980719e+08\n",
       "2014-09-23    3.366748e+08\n",
       "2014-09-24    3.321948e+08\n",
       "2014-09-25    2.947106e+08\n",
       "2014-09-26    2.505384e+08\n",
       "2014-09-27    2.318269e+08\n",
       "2014-09-28    2.574471e+08\n",
       "2014-09-29    3.025702e+08\n",
       "2014-09-30    3.387019e+08\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#平稳了之后 就可以使用模型来预测了\n",
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "#ARIMA是有三个值p q d  p是AR模型那个参数  q是MA模型那个参数  d是差分\n",
    "#这里可以先选一组值 （7,1,5） 来试试\n",
    "model=ARIMA(purchase,order=(7,1,5)).fit()\n",
    "purchase_pred=model.predict('2014-09-01','2014-09-30',typ='levels')\n",
    "#type='levels' 这里是用原始数据进行预测   如果不写表示用差分之后的数据预测  如果不写这句 是有可能出现负值的 相当于进行了反差分\n",
    "purchase_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16669.646033929606"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.aic#看一下model的AIC值 以确定模型的好坏 越小越好"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:162: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  % freq, ValueWarning)\n",
      "/opt/conda/lib/python3.7/site-packages/statsmodels/tsa/base/tsa_model.py:162: ValueWarning: No frequency information was provided, so inferred frequency D will be used.\n",
      "  % freq, ValueWarning)\n",
      "/opt/conda/lib/python3.7/site-packages/statsmodels/base/model.py:548: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available\n",
      "  'available', HessianInversionWarning)\n",
      "/opt/conda/lib/python3.7/site-packages/statsmodels/base/model.py:568: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
      "  \"Check mle_retvals\", ConvergenceWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "2014-09-01    3.169090e+08\n",
       "2014-09-02    3.372455e+08\n",
       "2014-09-03    3.632442e+08\n",
       "2014-09-04    3.074694e+08\n",
       "2014-09-05    2.628057e+08\n",
       "2014-09-06    2.258706e+08\n",
       "2014-09-07    2.592158e+08\n",
       "2014-09-08    3.115468e+08\n",
       "2014-09-09    3.477437e+08\n",
       "2014-09-10    3.562431e+08\n",
       "2014-09-11    3.092719e+08\n",
       "2014-09-12    2.598512e+08\n",
       "2014-09-13    2.339112e+08\n",
       "2014-09-14    2.578186e+08\n",
       "2014-09-15    3.125493e+08\n",
       "2014-09-16    3.537239e+08\n",
       "2014-09-17    3.573622e+08\n",
       "2014-09-18    3.146179e+08\n",
       "2014-09-19    2.626592e+08\n",
       "2014-09-20    2.387440e+08\n",
       "2014-09-21    2.616172e+08\n",
       "2014-09-22    3.157165e+08\n",
       "2014-09-23    3.588117e+08\n",
       "2014-09-24    3.611535e+08\n",
       "2014-09-25    3.197931e+08\n",
       "2014-09-26    2.672031e+08\n",
       "2014-09-27    2.432839e+08\n",
       "2014-09-28    2.661170e+08\n",
       "2014-09-29    3.197114e+08\n",
       "2014-09-30    3.635485e+08\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model2=ARIMA(redeem,order=(7,1,5)).fit()\n",
    "redeem_pred=model2.predict('2014-09-01','2014-09-30',typ='levels')\n",
    "#type='levels' 这里是用原始数据进行预测   如果不写表示用差分之后的数据预测  如果不写这句 是有可能出现负值的 相当于进行了反差分\n",
    "redeem_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "16519.896275849063"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model2.aic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.4预测结果可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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WyN/JvfkJCNJpsLe8lYkdeYTDIbH/YivuyTFNabC4JyxLj0FyVDB2n29mYkezFuhlmAATO5/067JraOkdwfMPL57yG1ev1WD5vFgcr+30cHREs3fyaie+u+cKrrT2Yfm8WDy9PR8Fye/t+ropPxH/uL8SB6+046/X3LkcmWi2vvPaZfzx7HUMuBK5TFMYti9OxsqMOKycF4v4WSRytwoP0mFDbjz2lrfiW9vyoQ3QixTynNP1XWjvG8W2RcmKxaDRCDy4OAX/UXoVnQOjN27cEc3EX8owA3cBg4mdj+noH8EvD9dic75zw/10rMky4nBVBVp6hifd20GkpOaeYfzj/grsK29FclQw/vXRJXhgQdKELd/nGcOQHR+ONy8zsSPPq2nvx2+P1+PevHjsWJyCFRmxiI9wXyI3ke2LknHgUhtOXu3E6iyjR1+LAs/e8lYE6zXYmBuvaBw7Fifj347WYf/FVnx81VxFYyHf9pcyzGilQ1EMB4f4mJ8erMaozYEntuZN+7GrM50XBsdq2R2T1GV4zI5/fqsaG39yBG9daccXN2bj0FfuwbaFybed47W5IME192vMi9FSINp9vgUaAfzjBxdg+6Jkjyd1ALB+fjxCDVrsKW/1+GtRYLE7JA5casXG3ATFm5bkJUVifkIEdp1vUTQO8m39I1aUVAfmUPKbMbHzIRWtffjD6SZ8YtVczDOGTfvxuYkRiA0z4HgdyzFJHcZbbd/7/FH881s12JiXgLe/eg++vCkHIQbtHR+/OT8RdofE25UdXoiWApWUErsvNGNNltErCd24EIMWm/ITcOBSK6x2h9del/zfyaudsAyMqaZk7cHFyTjb0I2mriGlQyEf9VZFO8bsgV2GCTCx8xlSSjy3rwIRwXp8YWPWjJ5DoxFYlRmHY7UWSCndHCHR9FS09uGRF07gcy++i8gQPV7+9Er84tGlN2Z5TcWClCgkRAbhzcvtHoyUAt27jd1o6hrGzsXeb+6wbWEyeoasrLQgt9pT3opQgxbr5ytbhjnuQdc+v9cucNWOZmZfeVvAl2ECTOx8xpEqM8pqLfjixuxZzaFbm2VER/8o6swDboyOaOq6Bsfw5KsX8cDPSlHd3o9ndxZi7+fXTnvPKOC8WbEpPwElNWaMWO0eiJYI2HWuBcF6De4r9P5cpKIcIyKCddhzgeWY5B5WuwOvX2rFvXkJU6qM8IbU2FAsS4/BrnPNvPFM08YyzL9gYucDbHYHnttfgXnGMHxsZfqsnmvNjX12LMck77LZHfjtsWu458eH8bKrpPjIV9fjYyvTZ9Xxb3N+IobG7FzRII+w2h3Yd9F5ERyuwF6kIJ0W9xUk4s3LbRi18eYFzd7xuk50D1mxTWUlazuWpKCmYwAVrf1Kh0I+hmWYf8HEzge8dLoJtR0DeGJLLgy62Z2ytLhQzIkJ4UUwedWxWgu2/qwU39lzBQvnROPAF9fhOw8WICp09rOTVmbEISJIx3JM8ojSGjO6BscUKcMct31RMvpHbThaZVYsBvIfey+0ICJIh+L5JqVDeY8HFiRBpxHYfaFZ6VDIx7AM8y+Y2Klc34gVPz1YjZUZsdiUn+CW51yTacSJq52wO1juQJ7V2DmEz/zPGTz2nycxbLXj3z9+F/7nk8uRkxDhttcw6DS4Jzcehyrb+Z4mt9t1rgXRoXoU5Sh3Ebw6Mw4xoXp2x6RZG7M58MblNmwqSECQTh1lmONiwwwoyjFhz/kWOPhZTlM0Xoa5dQHLMAEmdqr3i8O16B4aw1MP5N+27ft0rM6KQ9+IDZeae93yfES3Ghy14cdvVOLenx5FaY0FX7tvPg5+uRj3FSS67X18s835CbAMjOFcY7fbn5sC1+CoDQevtOOBBUmzrpaYDb1Wgy0LkvDWlXYMjdkUi4N8X1mtGX0jNtWVYY7bsTgZLb0jOF3fpXQo5CPGyzC3LlDne9rbmNipWFPXEP6rrB4PLZ2DwpQotz3vjXl2dSzHJPeSUmLXuWZs+MkR/OJwHR5YkIS3v3IPPrc+C8F6z90dvme+CXqtwJtXWI5J7vPmlTYMW+3YoWAZ5rjtC5MxbLVztAfNyt4LrYgK0WNtlrrKMMdtyk9AiF7LmXY0ZSzDfC8mdir2g9crodUIfHXzfLc+rykiCPMTIrjPjtzux29U4Ut/OI+EyGD86W9X4acPL0ZilOfnfkUE67Eq04g3L7exoxq5za5zLUiJDsGy9BilQ8HyebEwRQRhL7tj0gyNWO1480o77itIUHQF+nZCDTpsLkjA/outGLNxdiPdXh/LMN9HnX+zCWcburCvvBWfKc7wyIXx6qw4nKnvZot4cpvhMTv+50QD7i9IxK7PrsFd6bFeff3N+Qmo7xxCbQdHedDsWQZGUVZrwYOLk1VxwaDVCOcKeFUH+kesSodDPuhotRkDozZsW5isdCi3tXNxCnqHrThazWZBdHuHWIb5PkzsVMjhkPje3gokRAbh00UZHnmNtVlGjNoceLeBe5LIPfaUt6B/xIbH185T5EJ4vLkQyzHJHfaVt8LukIp2w7zV9kVJGLM58FYF3+M0fXvLWxEbZsDqzOnPDPWmtdlGxITqsfs8u2PS7bEM8/2Y2KnQnvIWXGjqwdfuy0WowTNzk5bPi4VWI7jPjtzmxZONyIoPx91zlSlbS4gMxqLUaCZ25Ba7zjcjNzEC8xPd18F1tpakxiAlOoTDymnahsfsOFTRjvsLE6HTqvvST6/V4IGFSXiroh0Do2wWRBNjGebE1P23OwCNWO340etVKEyJxAeXeO5OcUSwHovmRHFQObnF5ZZenG/qwaPL0zzS9XKqNucn4EJTD9p6RxSLgXxfQ+cgzjX2YKcHP4NnQqMReGBhEkprzOgZGlM6HPIhh6s6MDRmV203zFvtXJyCEasDb15uUzoUUimWYU6MiZ3K/LrsGpp7hvHk1nyP34FYk2VE+fUe9HG/Bs3SiycbEaTT4KGlcxSNY7OrHPMgS9VoFnafb4EQwIOL1LcXafvCZFjtEm/wgpemYW95C4zhQVgxT91lmOOWpjlXp9kdkyazr7wNySzDfB8mdipi7h/FLw/XYlN+AlZ5oQZ+daYRDgmcvMp5MTRzA6M27DrXjG0LkxEVqlc0lqz4cMwzhuEgyzFphqSU2HW+GcvnxiI5OkTpcN6nMCUSc+NCWY5JUzY4asPblR3YuiARWh8pWdNoBHYsTsaxWgvM/aNKh0MqM16GuYVlmO/DxE5Fnj9YjVGbA09syfXK6y1Nj0awXsOxBzQrr51vweCYHY+tTFM6FAghsDk/Ae/UWbgSTTNyqbkPV82DqivDHCeEwLaFyTheZ4FlgBe8dGdvVbRjxOpQfTfMW+1YnAK7Q2JfOVft6L1Yhjk5JnYqUdnWhz+cbsTHV6UjwxTuldcM0mlx99xYHGcDFZohKSV+f7IBuYkRqimH2JSfAKtd4kgVW2XT9O063wy9VmBroXovGLYvSoZDAgcuctWO7mxveSsSI4NVMY9xOuYnRiA3MQK7LzCxo/faV97KMsxJMLFTASklnttXgYhgPb64Mdurr70604jq9gF09LPZBE1f+fVeXG7pw2MrlG2acrMlaTEwhhtYjknTZndI7LnQgnvmxyteVnw78xMjkB0fjj3lTOzo9vpGrDha5budA3csTsG5xh40dA4qHQqphLMM08IyzEkwsVOBI9VmlNZY8IWN2YgONXj1tddkOffyHWd3TJqBF082ItSgVVXZmlYjcG9eAg5XdmDUZlc6HPIh79R1oqN/VFWz6yazfVEyTtd3sQMs3dZbV5wla9sWqXcF+nYeXOwsH32NTVTIhWWYtzelxE4IESuE2CSEMHo6oEBjszvw3L4KzI0LxcdXpnv99QuSoxAVouc+O5q2vhErXrvQggcXJSMiWF2rG5vyEzAwasMJNgaiadh9vhnhQTpszItXOpQ72rYwCVIC+1iOSbext7wVKdEhPluylhIdguVzY7HrfDOklEqHQyrAMszbu2NiJ4RIArAPwHIAh4UQptscmyCEOOfG+Pzey6ebUNsxgCe25sGg8/4CqlYjsCojDsfrOvmhSdOy61wzhq12PLbC+zck7mRNlhGhBi0OXmFLeJqaEasdr19qw/2FiQjWa5UO544yTOEoSI7EHu4/okn0DllRWmPGAwuTVFMqPxM7liSjzjyIyy19SodCCmMZ5p1NJZMoAPBlKeVzAN4AsPQ2x/4TAPX1h1apvhErfnqwGivmxd6Yv6WENVlxaO4ZRkPnkGIxkG+RUuLFk41YkBKFBXOilA7nfYL1WhTnmHDwSjscDt6woDt7u7ID/aM2nyjDHLdtYTLON/WgqYuf3fR+b1xug9UufWYo+WS2FiZBpxHYfb5Z6VBIYeNlmA/4+Hvak+6Y2Ekp35JSnhBCFMG5avfORMcJITYAGATAW+RT9MvDdegaGsO3tuUrejdtdZazwvYYu2PSFL3b2I3Ktn48ukL5EQeT2ZSfgPa+UZQ39yodCvmAXeeaER8R5JUZou4yfsG+l01UaAJ7yluQFhuKBSnqu/k2HTFhBtwz34TXLrTAzht1AY1lmHc21T12AsDDAKwA3teNQAhhAPBtAN+4zXN8WghxRghxxmxmG/KmriH8puwaPrhkDgoV/tDNMIYhMTKYDVRoyn5/shHhQTo8uEi9c5E25MZDqxEsx6Q76h2y4kiVGdsXJfvMAGcASI0NxZK0aJZj0vt0DozieF0ntvl4Gea4BxenoL1vFCev8TolUN1chukP72lPmVJiJ50+B+A4gG0THPINAL+QUvbc5jlekFIuk1IuM5km3aYXMH74eiU0GuBr981XOhQIIbA6Kw7H6ywsW6M76hkaw97yVuxckoywIJ3S4UwqOtSAFfNi8eZljj2g29t/qRVjdodPlWGO27YwGVda+1BnHlA6FFKR1y+3we6QPjeUfDKb8hIQatCyO2YAG+/wyjLM25tK85SvCyE+4fpjNICeCQ67F8DnhBBHACwWQvynuwL0R2cburG3vBWfKcpEYlSw0uEAANZkGtE9ZEVFGzcn0+396d1mjNkceHS5+pqm3GpzfgJqOgZwzcIZSDS5XeeakWEKQ2FKpNKhTNsDC5IgBLD3Assx6S/2lbciwxSGvKQIpUNxixCDFvcVJGL/xVaOsQlQ+y+yDHMqprJi9wKAjwshSgBoAVwXQjx78wFSyiIp5T1SynsAnJdSfsr9ofoHKSWe2XsF8RFB+ExxhtLh3LDGtc+O5Zh0O86mKQ1YkhaN/GT1XwTf62pKxHJMmkxLzzBOXuvCzsUpPlnekxgVjLvnxmJPeQs7GxMAwNw/ihNXO7HNz0rWdixORt+IDUequJ0n0LAMc+qm0jylW0q5yZW8fVZKeVlK+dRtjr/HrRH6mRdPNeJ8Uw++et98hBrUU8aWGBWMDFMYG6jQbZ281oU68yAeXa7epik3mxMTioLkSJZj0qRec+1PU/N+0TvZvigZtR0DqGrvVzoUUoEDl1rhkMA2H35PT2RtlhFxYQZ2xwxALMOcOu8PTgtgtR39eGbvFazLNuJDS+coHc77rM0y4tS1LozZHEqHQir14slGRAbrfGrfxub8RJxt7Ia5f1TpUEiFdp1rxuLUaMw1hikdyoxtKUyEhuWY5LL3QityEsKRk+AfZZjjdFoNti1MwlsVHegfsSodDnkRyzCnjomdl4za7Pj8S+cRatDhJx9epMrBiqszjRgas+N8U4/SoZAKdQ6M4sClVnxw6RyEGNQ/wHncpvwESOmcf0N0s6q2flS29WPnYt+5UTERY3gQ1mQZWY5JaOsdwemGLp+6+TYdDy5OwZjNgTdYhREwxsswt7IMc0qY2HnJj16vQkVrH378oYWIj1RHw5RbrcqIg0YAx2pZjknv98ez12G1Szym4tl1E8lLisCcmBAcvMILAXqv3eebodUIvyhZ27YwCQ2dQ7jIuY0Bbd/FVkgJnx9KPpmladFIjQ1hOWYAGS/D3Oqn72l3Y2LnBUeqOvDrsmv4f6vSsTEvQelwJhUVqkdhShSOc58d3cLhkHjpVCOWz41Fto+V9wghsDk/EaW1FgyO2pQOh1TC4ZDYfb4Fa7OMMIYHKR3OrN1XkAi9VnBYeYDbV96C/KRIZJjClQ7FI4QQ2LEoBcdqLejoH1E6HPIClmFODxM7DzP3j+Kr/3cB8xMi8MTWPKXDuaPVmUaca+zhBTC9x/G6TtR3DuFRH1utG7cpPwFjNgdKqtlNjZzONnajuWcYO5f4/mod4JzbWJRtwt4LLZxHGqCae4bxbmOP3zeY2LkkGQ7JPaWBgGWY08fEzoOklPjaHy+gb8SGn310CYL16t+XtCYrDjaHxKn6LqVDIRV58VQDYkL1uL8wUelQZuTuuTGIDtWzHJNu2HWuGSF6LTbn++Z7eiLbFiWhpXcE55q6lQ6FFLCv3Nnhdbuf7q8blxUfgfykSOy+wGHl/o5lmNPHxM6Dfnu8HkeqzHjqgTzMT/SN8rVl6bEwaDU4zn125NLRP4I3L7fjQ3fN8YmbExPRaTXYmJuAQ5UdsNrZ9TXQjdkc2HexFZvyExAWpJ6xM7N1b14CgnQa7OFKRkDaW96KhXOikBYXqnQoHrdzSTIuNPXgmmVQ6VDIg1iGOX1M7DykorUP399fiY258fj4ynSlw5myEIMWS9OjcYyDysnl/85ch80h8VEfmV03mU35CegdtuL0Na5GB7qSajN6hqx+U4Y5LiJYj/Xz47HvYivsLMcMKA2dgyi/3uu3TVNutX1RMoQAXjvPVTt/xTLMmWFi5wHDY3Z84aVziArV40cfWuhzb8g1mUZcae1D1+CY0qGQwuyupimrM+N8fjN+UY4RQToN3mQ5ZsDbdb4ZMaF6rMs2KR2K221flAxz/yhOXuPNuUAy3jTnAT8vwxyXFBWCFfNisft8M0d8+CmWYc4MEzsPeG7/FdR0DOD5jyxCnA92W1uTbQQAvFPHC4NAV1JjxvXuYZ9tmnKzUIMO67JNOHilnRcCAWxg1Ia3KtrxwMIk6LX+90/ghtx4hBq0LMcMMHvLW7E0LRop0SFKh+I1Oxan4KplEJea+5QOhTxg/8VWpESHsAxzmvzvXzWFvXm5Df97ohGfLsrw2bvBC1OiEBGkwzGOPQh4L55shDHc4DcNJjbnJ6C5ZxiXW3ghEKjeuNSGEasDOxenKB2KR4QYtLg3LwGvX2rlftIAUWceQEVrn98OJZ/MlkLniI9dnGnnd8bLMLcUJvpc1ZvSmNi5UVvvCP7hT+UoTInEVzfPVzqcGdNpNViREctB5QGutXcYb1d24MPLUmHQ+cdHxca8eGgE2B0zgO0634w5MSG4Kz1G6VA8ZtvCJHQPWfkZHiD2lbdCCGDrgsAqWYsONeCe+fHYc6GFe0r9DMswZ84/rtZUwOGQ+PtXzmPU6sC/PLLE5y+EV2ca0dA5hOvdQ0qHQgr5w+km2B0SH73b98swx8WFB2FZeiz32QUoc/8ojtVasGNxsl/fBS6eb0JEsI7DygPE3vIW3J0ei8SoYKVD8bodi5PR0T+KE1e5dcSfsAxz5nw7+1CRF0qv4nhdJ77zYD4yfbzJBACsyXLuszvO7pgByWZ34A+nm1CUY/K71tmb8hNQ0dqHpi7etAg0e8tb4JDw2zLMcUE6Le4rSMQbl9swarMrHQ55UHV7P6rbB7BtUWCubNybl4Awgxa7WY7pN1iGOTtM7Nyg/HoP/umNKmxdkIiPLEtVOhy3yEkIhzE8iPvsAtThKjNae0fwqI+POJjIpvwEACzHDES7zrcgPykS2Qm+MVd0NrYtTEL/iA0l1fwM92d7L7RAI4AthYGZ2AXrtbivMBEHLrZhxMqbGP6AZZizw8RulgZHbfjCS+cQHxGE73/A90YbTEYIgdWZcThe18kOggHoxZMNiI8Iwsa8eKVDcbu5xjDMT4jAm1falA6FvOiaZRAXmnr8bnbdZNZkGRETqseeC5zz5a+klNhb3oqVGXEwRfheB2532bk4Bf2jNhyp6lA6FHKDfeUsw5wNJnaz9J3XLqOhawg/fXgxokL1SofjVmuy4mDuH0VNx4DSoZAXXe8ewpFqMx65O9Uv28EDzlW7U9e60M1ZjQFj9/lmCAE8uMi/yzDH6bUa3F+YhLcq2jE8xpUMf1TR2o+rlsGA64Z5q9WZcTCGG7DrHG9i+Lq+EStKa1iGORv+edXmJXsutOD/zl7H363PwoqMOKXDcbvVmc59duysFlhePtUEAeBhPyzDHLe5IAEOCbxdyTu8gUBKid3nW7ByXlxANZjYvigJQ2N2vs/91N7yFmg1AvcX+sc4mpnSaTXYtjAZb1d1oHfYqnQ4NAvjZZgPsAxzxpjYzdD17iF889WLWJIWjS9szFY6HI9IjQ1FelwojrGBSsCw2h34w5kmrJ8f79eDbhekRCExMpjlmAGi/HovrlkGA6YMc9yKec4SPZZj+p/xMszVmXGIDTMoHY7idixOxpjNgTcu8TPdl42XYS5mGeaMMbGbAZvdgS+9fB5SAv/y8BK/LVcDnKt2J692wsZBtwHhrSvtMPeP4tEV/rtaBzj3kG7KT0BJtYUb7gPArvPNMLhKEwOJViPwwIIkHK7qQP8IVzL8ycXmXjR2DWF7gJdhjlucGo30uFDsvsDumL6KZZju4b8ZiQf96+FanGnoxrM7C/2uFfyt1mTFoX/UhovNvUqHQl7w4qlGJEcF4575/tc05VabCxIwbLWjrIalxv7MZndgz4VWrM81ISrEv/ZBT8W2hUkYtTnwVgW7wPqTveWt0GsF7isI7DLMcUII7FiUjON1nWjvG1E6HJoBlmG6BxO7aTpT34WfHarBB5akYOcS/9+Ev8q1d5D77PxfQ+cgSmsseGR5GrQa/79btmJeHCKCdSzH9HPH6zphGRj1+9l1k1maFoPkqGDsvcBh5f5CSol95a1Yl23yu6Zts/Hg4hRICZYe+yiWYboHE7tp6B224osvn0dKTAi+t6NA6XC8Ii48CHlJkdxnFwBePNUIrUbg4bv9YxbjnRh0GqyfH49DFR2wOzjSw1/tPt+CiGAd1uf6/yr0RDQagW2LklFSY0bvEMsx/cG7jT1o7hnGNq5svEdWfDgKUyKx+zwTO1/TO8wyTHdhYjdFUko8+epFtPWN4F8eWYKI4MC5S7YmMw5nG7u5F8mPjdrs+OOZ67g3Lx4JkYHTNXBzQQI6B8fwbmO30qGQB4xY7Xjjchu2FCYiWK9VOhzFbFuYBKtd4o3LXJ32B/vKW2HQabApP0HpUFRn5+IUXGzuRZ2ZY5p8Ccsw3YeJ3RT96d1m7C1vxd9vysHStBilw/GqNVlGjNkcOFPPi19/9cbldnQOjuHRFelKh+JVxTkmGLQavMkLXr/0VkU7BkZtAVuGOW5BShTS40Kxp5wrGb7O4ZDYf7EVxTmmgLrBPFXbFiZDCHDVzsfsv8gyTHdhYjcF9ZZBfHv3JayYF4v/rzhT6XC8bvm8WOg0AsfquM/OX714sgGpsSFYl2VUOhSvigjWY1VmHN680g4pWY7pb3ada0FCZJBfzhmdDiEEti1MwrFaCywDo0qHQ7NwpqEbbX0jLMOcRGJUMFZlxOG18838TPcR42WYWxewDNMdmNjdwZjNgS+8fA56rQY/fXhxQDSVuFVYkA6LU6NxnA1U/FJtxwBOXO3CR5enQROA7+/NBQlo6BxCTQdLd/xJz9AYjlZ34MFFyQH5uX2r7YuS4ZDAAc758ml7y1sQrNfg3jyWYU5mx+Jk1HcO4cJ1dvP2BeNlmFsX8GaFO0wpsRNCxAohNgkhAut2PoCfvlWN8uu9+MEHFyDZjwc238maLCMuNveid5ib7/3NS6caodMIfPiuwGiacqtNrgsklmP6l30XW2G1S+wI8DLMcfMTIpAVH86OgT7M7pDYf7ENG3LjERakUzoc1bq/MAkGrQa7z3OmnS9gGaZ73TGxE0IkAdgHYDmAw0II0wTHRAkhDgghDgohXhVCGDwQq9cdr7Xg347W4aPLU7ElwO8krMkywiGBE1fZHdOfjFjt+NO713FfYSJMEUFKh6OI+MhgLEmLxptXOOfLn+w+14Ks+HAUJEcqHYoqCCGwfWEyTtd3oa2Xc7580cmrztEd2ziU/LaiQvRYn2vCngutsNkdSodDt8EyTPebyopdAYAvSymfA/AGgKUTHPMYgOellJsAtAG4330hKqN7cAxffuU85hnD8K1t+UqHo7jFqdEI0WtZjuln9l9sRc+QFY8tT1M6FEVtyk9A+fVetPYOKx0KucH17iGcqu/CjkXJvFi4ybZFSZDSuZpJvmfvxVaEGrRYPz8wR3dMx87FKbAMjOId3oxWNZZhut8dEzsp5VtSyhNCiCI4V+3emeCYX0opD7r+aALQ4d4wvUtKia//qRxdg2P42SNLEGpgyYNBp8HyebE4VscPSX/y4slGzDOGYVVmYDeX2JyfCMD5jwz5vtdc5YYsw3yvTFM48pMisZfdMX2Oze7A65fasDEvASGGwB3dMVXrc+MREaRjd0yVYxmm+011j50A8DAAK4BJh5kJIVYBiJFSnpjge58WQpwRQpwxm80zjdcrXjzViDevtOPr9+eiMCVK6XBUY01WHGo7BljG4yeq2vpxpqEbjy5PC/hVjaz4cGSYwliO6Sd2n2vB0rRopMWFKh2K6mxflIxzjT1o6hpSOhSahuN1negaHGM3zCkK1muxPjceR6o64HCwO6YajVjtKKu1YFN+QsBfg7jTlBI76fQ5AMcBbJvoGCFELICfA3h8kud4QUq5TEq5zGR63zY91ahp78cze69gXbYRj6+Zp3Q4qrI609k75zjHHviFF082wKDV4KG75igdiipsyk/AO3WdbBDk4yrb+lDV3o+dS7haN5HxxIDlmL5lb3kLIoJ0KM5R7/WT2hTlmGAZGMOV1j6lQ6EJnG3oxqjNwfe0m02lecrXhRCfcP0xGkDPBMcYALwC4AkpZYM7A/SmEasdX3j5PMIMOvzkI4sCsvX77eQnRSImVI9jtSzH9HVDYzb8+Vwzti5IRGyYX/Q6mrXN+YmwOSSOVPl0JXnA23WuBVqNwAPcszGh1NhQLE6NZndMHzJmc5ZhbspPQLCeZZhTVZTtvBldUqPuKrFAVVJjhl4rsCIjVulQ/MpUVuxeAPBxIUQJAC2A60KIZ2855pMA7gLwpBDiiBDiYTfH6RU/er0KFa19+PGHFyI+IljpcFRHoxFYlRmH43UWDv70cXsvtKJ/xIZHV6QrHYpqLEmNhjE8iOWYPszhkHjtfDOKso2ICw/MLq9TsW1hEi639OGqmbMbfUFZrRl9IzZsW8SbFdMRHxmM3MQIlFQzsVOj0moLlqXHso+Fm02leUq3lHKTlLJISvlZKeVlKeVTtxzzKylljJTyHtevP3guZM84XNWB3xy7hr9aPRcbcjn4czKrM41o7R3BNcug0qHQLPz+VCOy4sNx99wYpUNRDY1GYFN+PI5WmTFqm3QrManY6foutPSOsAzzDrYtTIYQwN5ylmP6gr0XWhEVosfaLJasTVfxfBPO1HdjYNSmdCh0E3P/KK609mFtdsCNx/a4Ke2xCwStPSNYkBKFb2zJVToUVVub5fxLyO6YvutScy8uNPXgsRVsmnKrzfmJGBi14R2+v33SrvMtCDVosSmfN+duJzEqGHenx7Ic0weMWO04eKUd9xUkwKDjJdt0FWebYHNIfqarzDHX6KyibN6scDd+Srg8uiINr352NevX7yA9LhQp0SGcZ+fDXjzViCCdBh9cwqYpt1qVGYcwg5blmD5ozObA/out2JyfwNKeKdi+KAk1HQOoautXOhS6jZJqM/pHbXiAQ8ln5K65MQjRa1mOqTIlNWbEhOpRkBypdCh+h4ndTXRa/u+4EyEEVmfG4Z2rnWwh7IMGRm3Yfa4Z2xYmIypUr3Q4qhOs16J4vglvXWnn+9vHHKnqQO+wFTtYhjkl9xcmQSPAVTuVe6uiHZHBOqwO8FmjMxWk02JVZhwbqKiIlBJlNRaszTaxSaEHMJOhaVuTZUTPkJUthH3Q7vPNGByz47GVaUqHolqb8xPR0T+KC9d7lA6FpmH3+RbEhhlulIvT7ZkigrA604i95S1shqVS4xfAa7KM0PPG84wVZRvR0DmEhk72BlCD6vYBdPSPYh3313kEPylo2sbvHB5jOaZPkVLixZONyE2MwJLUaKXDUa318+Oh0wiWY/qQ/hEr3qpox7aFSbwAnoatC5JQ3zmE2g52x1Sjq5ZBtPSOsMHELBW55qSxHFMdSl2rp0zsPIP/AtK0xUcGIzs+nA1UfEz59V5cbunDYyvT2TTlNqJC9ViREYs3L7cpHQpN0euX2jBqc2DHYpZhTkfxfOcF71Fe8KpSWY3z5uk6dsOclXnGMKTGhvB9rhIlNRZkxYcjKSpE6VD8EhM7mpE1WUacutbJtvA+5PcnGxBq0GLnYm7Cv5PN+YmoMw+ijnO+fMJrF1qQFhuKpWnRSofiU1KiQ5AdH84LXpUqrTEjLTYUaXGhSofi04QQKMo24Z26TozZHEqHE9BGrHacvNrJ1ToPYmJHM7I6Mw4jVgfONfYoHQpNQe+wFXsutOLBRcmICGbTlDsZb5d/kOWYqmfuH8WxWgt2LE7mSvQMFOeYcPJqF4bGOOdLTax2B05c7eIFsJsU5ZgwOGbH2YZupUMJaGfquzFqc3DMgQcxsaMZWZERB40Axx74iF3nmjFsteOxFelKh+ITkqNDUJgSyXJMH1BaY4ZDAvcVJCodik8qnm/CmN2Bk1e7lA6FbnK+qQcDozYmdm6yOjMOOo1gd0yFldaaodcKrMiIVToUv8XEjmYkKkSPhXOiuc/OR7xypgkLUqKwYE6U0qH4jM35iTjX1IOO/hGlQ6HbKKuxIDbMgPwkzkOaibvnxiJYr2E5psqU1ligEcCqTCZ27hARrMfStBg2UFFYabUFy9JjOWvUg5jY0YytyYrDBdddRVKv9r4RXG7pw9YFSUqH4lM2FyRASuBQRYfSodAkpJQoq7VgdWYc5yHNULBei1UZcUzsVKasxoyFc6IRFcLSeXcpnm/C5ZY+mPtHlQ4lIJn7R3GltQ/rcnizwpOY2NGMrck0wuaQOHWNq3ZqNn6HsjiHNe3TMT8hAqmxISzHVLHaDuc8JM6um53iHBOuWQY550sleoetuHC9l2WYbja+r6uU5ZiKGB+RxS6vnsXEjmZsaXoMgnQaHKtlYqdmR6vNMEUEIS8pQulQfIoQApvzE3GsrpOr0ipV6moHzzlfs1M8Px4A53ypxTt1nbA7JNaxwYRbFSRHIi7MwPe5QkpqzIgJ1aMgmWXznsTEjmYsWK/FsrkxHFSuYnaHs1StKNvEjoEzsDk/AWM2By8EVOpYrQVz40IxJ4bt4Gdjblwo0mJDWY6pEmW1ZoQZtFjC8R1updEIrM02orTGAodDKh1OQJFSorTGgrXZJpbNexgTO5qV1ZlGVLb1wzLAmnU1Kr/eg54hK4pY0z4jd6XHICpEz312KuRsB9/J1To3EEKgOMeE43WcTaoGZTUWrMyIg17LSzR3K8o2oXNwDFda+5QOJaBUtffD3D/K8mIv4KcGzcoa196Wd9gdU5VKqi0QAizpmSGdVoN75ptwpKqDd3hV5nxTDwbH7Nxf5ybFOSYMjdlxpp5zvpTU1DWE+s4h3rDwkPHGHVyd9q4yV9k8EzvPY2JHs7IgJQoRwTqWY6rU0eoOLEyJQmyYQelQfNaG3Hh0Do7hwvUepUOhm5SNt4PP4IWCO6zKjINBy7EHSiur5QWwJ8VHBCM/KZLl9V5WUmNBVnw4kqJClA7F7zGxo1nRagSKsk04VNkBO1c0VKV3yIrzTT3shjlLxTkmaDUCb1eyHFNNymotWDAnGlGhbAfvDmFBOtw9LwZHq3jBq6TSGjMSI4ORaQpXOhS/VZRjwtmGbjbF8pIRqx0nr3byZoWXMLGjWbu/MBHm/lGcbWAJj5qU1VrgkM5/xGjmokMNuCsthvvsVKR/xHnTYm1WnNKh+JXiHBOq2vvR2jusdCgBye6QOFbrvABmsyvPKcpxjmo6zkojrzhT341Rm+PGuAnyLCZ2NGvrc+MRpNNg/8VWpUOhm5RUmxERrMPi1GilQ/F5G/LicaW1jxe8KnHyahfsDom1nIfkVsU5HHugpEvNvegdtnJ/nYctS49FqEGLEs6z84rSGjP0WoEVGbFKhxIQmNjRrIUH6VCcY8Lrl9rYYEIlpJQ4Wm3GumwjdOysNmsbc50XvIcreSGgBmW1FgTrNViaHq10KH4lJyEciZHB3GenkPH9dWvYEMijDDoNVmXEoaSaK3beUFJjcSXTOqVDCQi84iO32LogCW19IzjPBhOqUNMxgLa+EZY+uElWfDhSY0PwdmW70qEQnBfAy+fFIUinVToUvzI+9qC0xgKb3aF0OAGntMaM/KRIGMODlA7F7xXlmNDYNYR6y6DSofg1c/8oKlr7bnQjJc9jYkdusSEvHgatBgdYjqkK4w0QuL/OPYQQ2DA/HmW1FoxYOedLSa29w6jtGMA6rmp4RPF8E/pHbDjf1KN0KAFlcNSGsw3dbDDhJeNNxViO6VnjHdPXsWzea5jYkVtEBuuxNtuI/RfbICXLMZVWUmNGdnw4kqPZWthdNuQlYMTqwDtXObNRScdqnf//Wa7mGWuyjNBqBMsxvezUtS5Y7ZL767xkrjEMabGh3E/qYSU1ZsSE6lGQHKl0KAGDiR25zZbCRDT3DONic6/SoQS04TE7Tl7r4pgDN1sxz7nh/m12x1TUsVoL4sIMyE2MUDoUvxQVoseS1Ggmdl5WWmNBkE6Du+eywYS3FOUYcbyuE2M2lh17gpQSpTUWrM02QaNhl1dvYWJHbrMpPwE6jcD+i21KhxLQTlxz/kPFMkz3CtZrsTbLiLcrO7gqrRApJcpqLViTZeSFggcV55hQfr0XloFRpUMJGGW1ZiyfF4tgPfeNektRtglDY3acaehSOhS/VNXeD3P/KMuLvYyJHblNdKgBq7OMeP1SKy98FXS0yoxgvQbL5/HOr7ttyI1Hc88wqtr7lQ4lIFW3D8DcP4q1LMP0qOL5zptCZTXsGugN7X0jqG4f4Pvay1ZlxkGnEeyO6SGlrv+vTOy8a0qJnRAiVgixSQjBs0O3taUwEfWdQ6ho5YWvUkpqzFgxL453fj1gvWvswduVLMdUwo128LxQ8KjC5CjEhhlYjukl4wk099d5V0SwHkvTY7jPzkNKay3Ijg9HUhT3+nvTHRM7IUQSgH0AlgM4LISYsL5LCPFrIcRxIcRTbo6RfMjm/ARoBHDgErtjKqGpawhXzYPcX+chCZHBWJASxX12CimrMSPDGIYUNgXyKI1GoCjbiJJqM2eTekFpjRlxYQbkJbLBhLcV55hwpbUP5n6WHbvTiNWOk1c7ebNCAVNZsSsA8GUp5XMA3gCw9NYDhBAfBKCVUq4GkCyEyHZvmOQr4sKDsDIjDvs59kAR462bub/Oc9bnxuPdxm50DY4pHUpAGbM5cPJaF7theknxfBM6B8dwuaVP6VD8mnPfqPMCmPtGvW/8Jmgpxx641Zn6bozaHJylq4A7JnZSyreklCeEEEVwrtq9M8Fh9wB4xfX7twGsvfUAIcSnhRBnhBBnzGb+BfJnWxYkoc48iBruQ/K6o1VmpESHINMUpnQofmtjbjwcEjhazVU7bzrX2I2hMTvvAHvJOtcFGd/nnlXZ1g/LAPeNKiU/KRJxLDt2u9IaM/RagRUZ3OvvbVPdYycAPAzACmCi6bxhAJpdv+8DkHDrAVLKF6SUy6SUy0wmZvD+7L6CBAgBdsf0MqvdgeN1nSjKMcH5V5Y8YUFKFIzhQXi7khcC3nSs1gKNAFZmxCkdSkAwhgdhQUoUL3g9bHx/3TqubChCoxFYl21EaY2FZcduVFJjwbL0WIQadEqHEnCmlNhJp88BOA5g2wSHDAAY3/QQPtXnJf8UHxGMu9Njuc/Oy95t6MbAqI376zxMoxHYkGvC0aoOWO2cf+QtZbUWLEqNRlSIXulQAkZxjgnvNvagd9iqdCh+q7TWgqz4cCRGBSsdSsAqyjGhi2XHbmPuH0VFax/W5XAVWglTaZ7ydSHEJ1x/jAbQM8FhZ/GX8stFAOrdEBv5sC0LElHZ1o8684DSoQSMo9VmaDUCq7O4ouFpG3Lj0Tdiw9mGbqVDCQh9I1ZcuN7LcjUvK55vgt0hcbyW7eA94UaDCb6vFTW+WlrCfXZuccz1ecH9dcqYysraCwA+LoQoAaAFcF0I8ewtx+xyHfM8gI/A2UWTAtj9hYkAgNcvsRzTW0pqzLgrLQaRwVzR8LS12SbotYJjD7zkRF0n7A7JxiletiQ1GhHBOpZjesjZBmeDCc75UpYpIggFyZF8n7tJSY0ZsWEG5Cexy6sSptI8pVtKuUlKWSSl/KyU8rKU8qlbjumDs4HKCQDrpZS9ngmXfEVSVAiWpkWzHNNLzP2juNTchyKWPnhFeJAOKzPimNh5SVmtBSF6LZamxSgdSkDRaTVYm2XE0WozpOT+I3crrbFArxXcN6oCRTkmvNvQjf4Rlh3PhpQSpTUWrMlil1eluG0vnCsBfEVKySUaAgBsXZCES819aOwcUjoUv1dW67zTWJwTr3AkgWNDbjxqOwbQ0DmodCh+r6zWghUZsTDouH3b24pzTGjtHUFNB8vq3a2s1owlaTEIC2KDCaUVZZtgc0gcr+tUOhSfVtXeD3P/KFehFcR/Jclj7itwlmNy1c7zjlY5B9wWJLP0wVs25DqTaK7aeVZLzzCumge5D0kh4zMxj1axTM2dxpt1rOP7WhXuSo9BmEGLEpZjzkpp9XiXV76vlcLEjjwmNTYUC+dEYT/32XmUw+EsfVjHAbdelR4XhkxTGBM7DytzbcTn/DplJEeHICchnPuP3OxYrQVS8n2tFgadBqsy41BSw7Lj2SipMSM7PhxJUSF3Ppg8gokdedSWwiRcaOpBc8+w0qH4rcstfegcHLtxZ528Z2NeAk5e7cLAqE3pUPzWsVoLjOFBmJ8QoXQoAas4x4RT17owNMb3ubuU1pgRGazDwjnRSodCLsU5JjR1DaOe20dmZMRqx6lrXbxZoTAmduRRW9gd0+PGWzRzwK33bciNx5jdcWPIMLmXlBLHai1YmxUHIbgarZTiHOf7/MRV7j9yByklymosWJ1phJZVFqoxfnOU5Zgzc6be2eWVYw6UxcSOPGquMQz5SZE4cJH77DzlaJUZBcmRMEUEKR1KwLkrPQYRwTq8XdmudCh+qbKtH5aBMY45UNiyuTEI0Wu5z85NrloG0dI7wgHOKpMeF4b0uFAmdjNUWmOGXiuwIiNW6VACGhM78rgthYk409CNtt4RpUPxO30jVrzb2I1ilmEqQq/VoDjHhMNVZjgc3Jfhbse4v04VgvVarMqM4z47Nxlf4V+Xxc9ttSnKNuGdq50YtdmVDsXnlNRYsCw9FqEGdnlVEhM78rgtC5IAAG9cZjmmux2v7YTNIZnYKWhjXrxzjmALx3e6W2mNBZmmMG7EV4F75ptQ3zmEegvHe8xWaY0FabGhSIsLVToUukVRjglDY3acre9WOhSf0tE/gorWPq5CqwATO/K4rPhw5CSEYz/LMd2upMaM8CAdlqZzcLNSinPioRHAoQp2x3SnUZtrIz7LMFVh/ObR+J5emhmra68iV6HVaVVmHHQagaN8n0/LeHUF99cpj4kdecWWwiScru+CuX9U6VD8hpQSR6vMWJ0ZB72Wf5WVEhtmwJK0GI49cLNzjT0YttqxlhcKqpAeF4a5caHcZzdL55t6MDBq4/w6lQoP0mHZ3BiUVLMh1nSU1lgQG2ZAfhJn6SqNV4PkFVsWJMIhgTevsBzTXa5aBtHcM8wxByqwITceF5t70dHHfaTuUlZjgVbDjfhqUpxjwvE67j+ajdIaCzQCWJ3JxE6tinJMqGjtQ0c/P8+nQkrnLN01WZylqwZM7Mgr5idEIMMYhgMXmdi5y/idc+6vU97GvHgAwOEqrtq5S1mtBYvmRCEyWK90KORSPN+EYasdp69x/9FMldWYsXBONKJC+b5Wq/FywlKu2k1JVXs/zP2jWMfyYlVgYkdeIYTAlgWJeOdqJ7oGx5QOxy+U1JiRYQxDaiw34CttfkIEUqJDuM/OTXqHrCi/3sMyTJVZmREHg1aDo9V8n89E34gVF6738gJY5fKTImEMN3A/6RSNJ8B8X6sDEzvymi2FSbA7JA6yHHPWRqx2nLjayTJMlRBCYH2uCWW1FpapucE7VzvhkGDjFJUJNeiwfF4sxx7M0Dt1nbA7JN/XKqfRCKzLNqG0xsIxNlNQUmNGdnw4uxerBBM78pqC5EikxYbiwCUmdrN1ur4LI1YHyzBVZGNuAobG7Dh5tUvpUHzesVoLQg1aLE6NVjoUukVxjgnV7QNo6RlWOhSfU1pjRqhBiyVp7GKsdkU5RnQNjnGMzR2MWJ3di9exukI1mNiR1wghsKUwEcdqLegdsiodjk87WmWGQadhYwkVWZUZh2C9ht0x3aCs1uIs+9Pxnyi1KZ7vGnvAVbtpK6vh+9pXjCcqfJ/f3un6LozaHCzDVBF+upBXbVmQBKtd4q2KdqVD8WklNWYsnxuLUINO6VDIJVivxZpMIw5VtkNKlu/M1PXuIVyzDGINy9VUyVlyFcxyzGlq6hpCfecQL4B9hDE8CIUpkRx7cAdlNRbotexerCZM7MirFs2JQnJUMA5c4rDymWrpGUZ1+wDLMFVoQ148mrqGUdsxoHQoPmt80C0vgNVJCIHiHBPKaiyw2h1Kh+Mzyvi+9jlF2Sa829iN/hFWGE2mpMaCZem8yawmTOzIq5zdMZNQUm3hh+UMlbo6dbFxivpsyHWOPWA55syV1XbCFBGE7PhwpUOhSRTnmNA/asP5ph6lQ/EZZTUWJEYGI9PE97WvKMoxweaQOF7XqXQoqtTRP4KK1j6sy+HNCjVhYkdet3VBIsbsDl78ztDRajMSI4ORk8ALBLVJigpBflIkDvG9PSMOh8TxWgvWZhkhBAfdqtXqLCO0GnFjlibdnt0hUVZrwdpsvq99ydK0GIQZtCw7nsR4dUURG6eoChM78rolqTFIiAzisPIZsNkdKKuxoCiHFwhqtSE3HmcbutEzxHmN01XR1ofOwTG2g1e5qBA9lqZF84J3ii4196J32MoyTB9j0GmwOsuIkmoz901PoLTagtgwA/KTIpUOhW7CxI68TqMRuL8gEYerOjA4alM6HJ9y4XoP+kZsKM6JVzoUmsSGvHjYHZIXvTMwfgeYjVPUrzjHhIvNvbAMjCodiuqV8X3ts4pyTLjePYxrlkGlQ1EVKSVKay1Yk2WERsObzGrCxI4UsWVBEkZtDhxhKc+0HK22QCM4uFnNFs2JRlyYAYdZjjltZbWdyIoPR2JUsNKh0B2M31wa3/NLkyutMSM/KRLG8CClQ6FpKubYgwlVtffD3D/KVWgVYmJHirh7biyM4QbsZ3fMaTlabcbi1GhEheqVDoUmodUI3DM/HkeqzbCxa+CUOQfddvKmhY8oSI5EXJiB++zuYGjMhrMN3bwA9lFpcaGYGxeKkhqOPbhZaTW7vKoVEztShFYjsLkgEYcrOzBitSsdjk/oHhxD+fUedsP0ARty49EzZMU5dg2csncbuzFidTCx8xEajUBRjgklNRY4HNx/NJmT17pgtUus5QWwzyrKMeGduk6M2nitMq6kxuyaaRmidCh0CyZ2pJithUkYGrNzL9IUldZaICU4v84HrMsxQqcROFTBcsypKquxQKsRWJkZp3QoNEXFOSZ0DY7hUkuv0qGoVmm1BQadBnfP5QBnX1WUbcKw1Y4z9d1Kh6IKzuqKLqxjN0xVYmJHilmREYuYUD0OXGQ55lSUVJsRHarHwjnRSodCdxAZrMfyebHcZzcNx2otWJIajfAgDrr1FeuyjRACLMe8jbJaM5bPjUWwXqt0KDRDqzLjoNcK7rNzOV3fhVGbg2WYKsXEjhSj12qwOT8Rhyo6WOJwB1I6uyyudc2PIvXbkBuPqvZ+NHUNKR2K6vUOWVHe3MuugT4mLjwIC1KiWHUxifa+EVS3D/AC2MeFBemwLD2W73OX0hoL9FqBFRlchVajOyZ2QogoIcQBIcRBIcSrQgjDBMfECCH2CyFKhRD/5plQyR9tWZCI/lHbjTbnNLGKVmcHKu6v8x0bcp1dAw9XcdXuTo7XOcuMeQHse4pzTHi3sRu9Q1alQ1GdMlfDDe6v831FOSZUtvWjo29E6VAUV1pjwbL0WIQaWF2hRlNZsXsMwPNSyk0A2gDcP8ExHwfwv1LKdQAihBDL3Bgj+bHVmUZEBOuwn8PKb6vE1VKc++t8R4YpHPOMYXib5Zh3VFZrQXiQDotSo5UOhaapOMcEhwSO1fHm3K3Kai2ICzMgL5EDnH1dUY4zOQ/07pgd/SOoaO3DuhzerFCrOyZ2UspfSikPuv5oAjDRVUongPlCiGgAqQAabz1ACPFpIcQZIcQZs5nL2eRk0GmwKT8Bb15uw5iNreEnc7TKjNzECCREcr6XL9mQG4/jdZ0YGrMpHYqqldVasDIjFnotdwf4msWp0YgI1nGf3S2klCit4QBnf5GX6JxDGOj77Marq4rYOEW1pvyvqBBiFYAYKeWJCb5dBiAbwBcAVAJ4X+sgKeULUsplUsplJhPfEPQXWwuT0DdiwztXO5UORZUGR20409DF1ToftDE3HmM2B47V8r09maauITR0DnF/nY/SaTVYl23E0WozpOTYg3GVbf2wDIyyDNNPaDQCRdlGlNaYYQ/g8R6l1RbEhhmQn8RVaLWaUmInhIgF8HMAj09yyD8C+P+klN+DM7H7a/eER4FgbbYR4UE6dsecxDt1nbDaJRM7H7RsbizCg3R4u7Jd6VBUa/wOMOfX+a7iHBPaXI1CyGl8fx33jfqP4vkmdA9Zcak5MMd7SClRwlVo1ZtK8xQDgFcAPCGlbJjksFAAC4QQWgArAATu7QyatmC9Fhvz4vHmlXbY7CzHvFVJjRkhei3umhujdCg0TQadBkU5Rrxd2cHVjEmU1lqQEBmErPhwpUOhGRpv6nS0mvtJx5XWWpDFAc5+ZW2Wc7xHoJZjjq9C82aFuk1lxe6TAO4C8KQQ4ogQ4mkhxLO3HPN9AC8A6AUQC+Al94ZJ/m5LYSK6Bsdw6lqX0qGoztFqM1ZnxiFIxzlIvmhDbgLa+0ZxuaVP6VBUx+GQOF7rvAMsBO8A+6qkqBDMT4hgO3gX5wDnTq5C+5m48CAUJkfdaGYWaLgK7Rum0jzlV1LKGCnlPa5f35VSPnXLMaeklAVSynAp5SYpJesxaFqKc+IRotdi/yWWY96s3jKIhs4hjjnwYffMN0EIsDvmBK609qF7yMoLYD9wz3wTTl/rxuAoGwW929CNESsHOPujohwj3m3sQd9I4I33KKkxI5ur0KrHFmSkCiEGLTbkxuP1S+0BvTH5Vhxz4PuM4UFYNCcah5jYvU8Z99f5jeIcE8bsDpxgEyyU1Fig0wisyIhTOhRys6JsE+wOieMB1hDLuQrdhXXshql6TOxINbYsSIRlYBRn6lmOOa6k2oy02FDMNYYpHQrNwsbceJRf74G5f1TpUFTlWK0FOQnhiOcYD59319wYhBq0LMcEUFZrxtK0GIQHcYCzv1ma7jyvgVaOebq+C6M2B+fX+QAmdqQa6+fHI0inwYFLHFYOAGM2B47XdXK1zg9syIuHlMCRKq7ajRu/A7w2i+9vfxCk02J1ZlzAJ3Zdg2O43NLHMQd+Sq/VON/nVYE13qO0xgKDVoMV82KVDoXugIkdqUZYkA7FOSa8fqkNDpZj4kxDF4bG7Nxf5wfykyKRGBnMfXY3OdvQjVGbA2uzWa7mL4pzTGjoHEK9ZVDpUBRzrNYCKdlgwp8V5ZjQ3DOMqwH0Pi+pNuOu9BiEGrgKrXZM7EhVti5IQlvfCM419SgdiuKOVpuh1wqsyuSFr68TQmB9bjxKaywYs3GkB+DcX6fTCCyfx/e3vyjOiQeAgF61K6uxIDJYh4VzopUOhTxkvIomUMYedPSPoLKtn2WYPoKJHanKhrx4GLQaDisHUFJtwV3p3KfhLzbmxmNg1IbT3EMKwHkBzH1I/iUtLhTzjGEBm9hJKVFaY8bqTCO0HODst1Jjne/zQEnsjrmaXBWxcYpPYGJHqhIZrMe6bCMOXGoLqPr1W3X0jaCite/GHXDyfWuyjAjSaXCoguWY3YNjuNTSizXshul3inNMeKeuEyNWu9KheN1VyyBaeke4vy4AFGUbceJqF0Zt/v8+L622IDbMgPykSKVDoSlgYkeqc39hIpp7hnGxuVfpUBRT4hoEWsTSB78RYtBiVWYcDlW2B/RNCwA4XtcJKcELYD9UnGPCsNUekCvTHOAcOIrnO9/nZ+q7lQ7Fo6SUKKmxYG2WERquQvsEJnakOpvyE6DTCOy/GLjdMY9Wm2GKCOIdMj+zMTceDZ1DAbXpfiJltRaEB+mwaE6U0qGQm63IiIVBp8HRqsAoU7tZaY0FabGhSI/jeBp/tzIjDgatxu/Ljivb+mEZGOVNOB/CxI5UJzrUgNVZRhy41BqQKxt2h0RZjRnrso0QgnfI/Mn6XGdp7eEA7455rNaClRlx0Gn5T5C/CTXosGJerN9f8N7K6hrOzgvgwBBq0GHZ3Bi/32dX6prXx1Vo38F/VUmVthYmoqFzCFda+5QOxesuNveie8jK+XV+aE5MKHITIwJ6n11j5xAau4Z4oeDHinNMqOkYQHPPsNKheM2Fph4MjNqwjvtGA0ZRjgmVbf1o7xtROhSPKa2xIDs+HElRIUqHQlPExI5UaXNBIrQagQMBWI5ZUm2GEMA6dqDyS+tz43G6vgt9I1alQ1FEmavDGhun+K9AawcPOPdFawSwOpPv60Ax3iXSX9/nI1Y7Tl3r4rWIj2FiR6oUG2bAinmx2B+A5ZhHq81YmBKF2DCD0qGQB2zMjYfNIVFabVE6FEUcq7UgMTIYmSbuQ/JXWfHhSI4KDqh9dmU1ZiyYE42oUL3SoZCX5CVFwBQRdKPZmb85Xd+FUZuD8+t8DBM7Uq0tC5Jw1TyImo4BpUPxmt4hK841dqOIZZh+a0laDKJD9ThU2a50KF5nd0gcq7NgLfeP+jUhBIrnm3Cs1gKr3aF0OB7XN2LFheu9LMMMMEIIFGWbUFZjht3hfzegS2ssMGg1WDEvVulQaBqY2JFq3VeQACGA/QE0rPxYnQUOCe6v82NajcD6+fE4UuWfFwO3c6WlDz1DVqzlBbDfK84xoX/UhnONPUqH4nHv1HXC7pDcNxqAinKM6B6y+uV4ppJqM+5Kj0GoQad0KDQNTOxIteIjgnH33NiA2mdXUm1GRLAOi1OjlQ6FPGh9bjy6BsdwvqlH6VC8qrTWWZrH/XX+b3WWEVqNwNFq/28UVFZjQahBiyVpMUqHQl62LtsEIfxvn11H3wgq2/pZhumDmNiRqm0tTERVez/qzP5fjimlxNFqM9ZmGdkG3s8VZ5ug1YiAG3twrNaC3ETnvhTyb5HBetyVFhMQYw9Ka8zOuWY6fm4HmtgwAxakRPldYjfe5KqIjVN8Dj+FSNXuL0wCALx+yf9X7Wo7BtDaO8L9dQEgKlSPZekxOBRAid2I1Y7T9d1crQsgxfNNuNTcB3P/qNKheExT1xDqO4dYXhzANucn4ExDN842dCkdituU1VgQG2ZAflKk0qHQNDGxI1VLjArG0rTogNhnN35nm4ldYNiQG4+K1j60BMisr9P1XRizOTjAOYCM7xUeH3Lsj8ZXNri/LnD99Zp5SI4KxpOvXoLND5oFORwSpbUWrM0yQqNhkytfw8SOVG/rgiRcbulDQ+eg0qF41NFqM7Ljw5ESzUGggWBjXjwA4O0AWbUrq7VArxXssBZA8pMiYQw3+HU5ZlmNBQmRQciKD1c6FFJIWJAOTz9YgMq2fvz2eL3S4czay6ebYO4fxeaCBKVDoRlgYkeqd39hIgDggB+XYw6P2XHyWhdX6wJIpikcabGhAbPPrqzGgqVp7LAWSDQaZzv4kmr/7AA7Pr7D2UCDKxuBbHN+AjbkxuOnB6vR2uu7VRjtfSP4/v4KrM6MwwMLkpQOh2aAiR2p3pyYUCycE4UDflyOefJaJ8ZsDo45CCBCCGzIjUdZrQXDY3alw/GorsExXG7p4z6kAFQ834TuISsu+WE7+MstvegZsrIMkyCEwHcfLIDNIfHs3gqlw5mxb+++hDG7A//4gQW8WeGjmNiRT9hSmIQL13txvXtI6VA84mi1GUE6DZazTC2gbMiNx6jNgXeuWpQOxaOO1zl/vjW8AA44a7OMEAJ+WY5ZWuN6X/OGBQFIjQ3F5zdkYd/FVp98v79+qRVvXG7Hl+7NwVxjmNLh0AwxsSOfsMVVjumv3TGPVjvbZQfrtUqHQl60IiMWoQYtDlX4dzlmWY0FEcE6LEyJUjoU8rK48CAsTInyyQvdOymtMSMvKRLGcI7vIKe/KcpAhikM3959CSNW36nE6B224lu7LyM/KRKfWjdP6XBoFpjYkU+YawxDflKkX3bHbOoawlXzIPfXBaAgnRbrso04XNkBKf1vDxLgnM9YWmPBqow4zmcMUMU5Jpxr7EbvkFXpUNxmaMyGsw3dLMOk9wjSafHsjkI0dA7hV0fqlA5nyn5woBKdA6P44UMLoefntE/j2SOfsW1REt5t7ME1i391xyxxtQLn/rrAtDE3AS29I6hs61c6FI9o7BpCc88wxxwEsA15CXBI4MVTjUqH4jYnr3XBapdM7Oh9VmcZsWNxMn51tM4nrldOXO3ES6ca8al1GVgwh1UVvo6JHfmMDy2dA61G4OXT/nNxAAAl1WakRIcg08Sa9kB0T64zoffXsQfj+5DYOCVwLU6Nxqb8BPzsUA2a/WRuY1mNBQadBnfP5b5oer8nt+YhSKvBt3dfUnU1xojVjif+fBFpsaH48r05SodDbnDHxE4IESWEOCCEOCiEeFUIYbjNsb8UQmx3b4hETvGRwdiYG48/nb2OMZvvDwEFAKvdgWO1nSjKYbvsQBUfEYyFc6JwqKJd6VA84litBclRwZjHzfgB7ent+QCA7752WeFIZs/cP4o/nr2OdVlG7oumCcVHBuMrm3NQWmPB/ovq7Q3w87drcM0yiH/8wAKEGPhe9gdTWbF7DMDzUspNANoA3D/RQUKIdQASpZR73Bgf0Xt8dHkaLANjfnMRfK6xBwOjNhTncDUjkG3Ijce5ph50DY4pHYpb2R0Sx+s6sTbbyBsXAW5OTCi+sDEbb15p9/nP7+/uuYzhMTue2JqndCikYh9fNRcFyZH43t7L6B9R3/7SKy19+PejV/Ghu+awVN6P3DGxk1L+Ukp50PVHE4D31QsJIfQA/gNAvRBih3tDJPqLohwTkqOC/WavxtHqDmg1AqtZphbQNuYmQErgSJV/lWNeau5F77CV7eAJAPDJtfOQHR+Op1+77LOzGw9VtGNveSs+vyELWfHhSodDKqbVCDz3gQXo6B/FP79Vo3Q472F3SHzjz+WIDtXjSd6g8CtT3mMnhFgFIEZKeWKCb38CwBUAPwKwXAjx+Qke/2khxBkhxBmz2f/aHpN3aDUCH7k7FWW1FjR1+f5Mu5JqC5amRSMyWK90KKSgguRIJEYG4+XTTarejzFdZbWc80V/YdBp8MzOQlzvHsYvDtcqHc60DYza8NSuS5ifEIHPFGcqHQ75gMWp0Xh0eRp+e7weV1r6lA7nhv86dg3l13vx9PYCxIRNusOKfNCUEjshRCyAnwN4fJJDlgB4QUrZBuB/Aay/9QAp5QtSymVSymUmE7v/0cx9ZFkqBIBXzjQpHcqsNPcM42JzL7thEjQagc+tz8Spa11484pvl6ndrKzGwjlf9B4rM+LwwSUp+PeSOtR2DCgdzrT8+PVKtPWN4PsPLYBBx95zNDX/cF8uokP0eGrXRTgcyt+4a+oawk/erMbG3HhsW5ikdDjkZlNpnmIA8AqAJ6SUDZMcVgsgw/X7ZQAmO45o1pKjQ1CcY8IrZ5pgs/tuE5XfHa+HViPwgaVzlA6FVOCjy9OQFR+O7++v8IvmQMNjdpxt6MbarDilQyGVeWJrHkL0WtV3DLzZ2YZu/O5EA/7fqrlYmhajdDjkQ6JC9fjm1jy829ij+A1pKSW++epFaATwzM5C7n32Q1O55fRJAHcBeFIIcUQI8bQQ4tlbjvk1gPVCiBIAnwXwT26Ok+g9Pro8De19ozhc5ZtlvYOjNrx0qhH3FyYiJTpE6XBIBXRaDZ58IA/1nUP4nxO+f2/s5LVOjNkdWJvNFWl6L1NEEL52fy6O13XitQstSodzR2M2B77xp3IkRQbjq/fNVzoc8kEfXJqC5fNi8YPXKxVtkvXquWaU1ljw9S25SOa1h1+aSvOUX0kpY6SU97h+fVdK+dQtx/RLKT8spSySUq6SUjZ7LmQiZxfB+IggvOyjTVT+/O519I3Y8PiaeUqHQipyT44J67KN+Je3qtHtwx0yHQ6Jnx2qQWyYAcs554sm8OjyNCyaE4Vn9lagT4UdA2/2qyN1qOkYwLMfKER4kE7pcMgHCSHw7M5CDIzY8MMDlYrE0Dkwimf2XsHStGh8bEW6IjGQ57FInHySTqvBh5fNweGqDrT2+tbAW4dD4jfH6rEoNRpL06KVDodURAiBpx7Ix8CoDf9ySF1d1KbjD2ea8G5jD765NY+zkWhCWo3AszsXoGtwFD95o0rpcCZV29GPXxyuxfZFydiQm6B0OOTDchIi8Ml18/CHM004U9/l9dd/Zu8VDIza8IOHFkKjYQmmv2JiRz7r4WVpcEjgldPXlQ5lWo5Ud+CaZRCPr5nL+nZ6n/mJEXhkeRr+90QD6sy+1VwCcN4V/sGBSiyfG4uHlqYoHQ6p2II5Ufj4ynT8z4kGXLzeq3Q47+NwSHzjTxcRGqS9MWCdaDa+uDEbyVHBeGrXJa/2CDhc1YFd51vw2XuykJMQ4bXXJe9jYkc+Ky0uFOuyjXjlTBPsKug0NVW/KatHYmQwti5gNyqa2JfvzUGwXovv71emZGc2fnCgEoOjNm7Mpyn5+83zERsWhKd2XVTd5/iLpxpxpqEbTz2Qz86u5BahBh2efrAAlW39+O3xeq+85uCoDU+9eglZ8eH47HqO6fB3TOzIpz1ydxqae4ZRUuMbTVSq2vpRVmvBJ1anQ6/lXz+amCkiCJ9dn4m3Ktpx3DULzhecru/C/529jk+unYf5ibwrTHcWFaLHt7bl4cL1Xrykoj3Tbb0j+MGBSqzNMnLlmdxqc34CNubG46cHq72yleSf3qxCS+8wfvjQAgTpWBrv73hlST5tU34C4sIMPtNE5Tdl1xCs1+Cjd6cpHQqp3ONr5iElOgTP7KtQ3UrGRKx2B5569RKSo4LxhY3ZSodDPuTBRclYnRmHH71eCXP/qNLhQEqJb+2+BJvDgec+wJVnci8hBL7zYAHsUuKZvVc8+lrnGrvx2+P1+PjKdNyVzkZWgYCJHfk0g06DD901B29VdKCjb0TpcG6rc2AUr55vxgeXzkFMmEHpcEjlgvVafGNLLipa+/Cns+rfR/rbY/Woau/H0w8WIIydA2kahBD43o5CDFvt+P6BCqXDweuX2nDwSjv+flMO0uPClA6H/FBqbCg+vyEb+y+24UhVh0dewzmm4yISI4PxNY7pCBhM7MjnPXx3KuwOif9T+cXviycbMWZz4PE1c5UOhXzEtoVJWJIWjR+/WYXBUZvS4UyqpWcYP32rGhty47E5n50Dafqy4sPx6aIM/PndZpy42qlYHL1DVnz7tcsoTInkOBryqE+tm4cMUxiefu0yRqx2tz//vx+tQ1V7P57dWYiIYL3bn5/UiYkd+bwMUzhWzIvFH043waHSkrUxmwO/O9GA4hwTsuK594imRgiBb23Lh7l/FP92tE7pcCb1zN4rsDskvvtgAcvWaMb+bn025sSE4Fu7LmHM5r2OgTf7/oEKdA2O4QcfXAgd90GTBwXptHh2RyEaOofwqyPu/Xyv7RjAz9+uxbaFSdiYx5ttgYSfWuQXHl2RhsauIRyvU+5O7+3sLW+BuX8Uj6/lHWCanqVpMXhwUTJeKLmKlh71zWw8XNWBA5fa8PkNWUiNDVU6HPJhIQYtvvtgAWo6BvDrsmtef/136jrx8ukmfGrtPBSmRHn99SnwrM4yYsfiZPzqSB2uWQbd8pwOh8QTfy5HiEGLp7cXuOU5yXcwsSO/cF9BIqJD9XjptPqaqEgp8euya8iKD0dRtlHpcMgH/cP98yEB/Fhlg5xHrHY8vfsyMkxh+JuiDKXDIT+wMS8Bm/MT8LNDNbjePeS11x2x2vHNVy8iLTYUX7o3x2uvS/TkA3kI0mnw7d2XIOXsq45ePNWI0/XdeOqBPJgiOKYj0DCxI78QrNfiA0tS8OblNnQOKN9V7Wan67txuaUPj6+ZxzI1mpE5MaH41Np5ePVcM8439Sgdzg2/PFyLxq4hPLujkG20yW2eftC5yvDdPZ7tGHiznx2qwTXLIL7/wQUIMfC9TN4THxGMr943H6U1Fuy72Dqr5xof07EmKw4fumuOmyIkX8LEjvzGR5enwWqX+NO76mqi8puya4gO1eMDSzgLiWbus+uzYAw34Nm9V9xyV3e2rpoH8G9Hr2LH4mSszuJKNLlPSnQIvnhvNg5eacdbV9o9/npXWvrwQslVfOiuOVjD9zIp4GMr01GYEonv7bmC/hHrjJ7j5jEd//iBBbyRHKCY2JHfyEmIwF3pMXj5dJMqLnwBoKlrCG9eacOjy9N4F5hmJTxIh69sno8zDd04cKlN0ViklPj27ssI0mnw5AN5isZC/unxNfOQHR+O7+y5jOEx93cMHGd37UeKDtXjya18L5MytBqBZ3cugHlgFD89WDOj5xgf0/HlezmmI5AxsSO/8sjdqbhqHsSpa11KhwIA+O3xemiEwCdWzVU6FPIDH1mWitzECHz/QAVGbZ672L2TPeWtKKu14Kv3zUd8RLBicZD/Mug0eHZnIa53D+NfD8/sQncqfnu8Hheu9+Lp7QWcL0qKWpwajUeXp+G3x6/hckvvtB47PqajIDkSn2STtoDGxI78yraFyYgI1uGlU8o3UekfseIPp5vwwMIkJEbx4pdmT6sRePKBPDR1DeO3x+oViaFvxIpn9l5BYUokPrYyXZEYKDCsyIjDB5em4IWSq6jt6Hf78zd1DeGf3qjChtx4bFuY5PbnJ5quf7gvFzGhBnxr16VpjW8aH9Pxw4c4piPQ8eyTXwkxaLFzcQr2X2pDz9CYorH88ex1DIza8NcccktutC7bhA258fjXt2sVaRT0/JvVsAyM4rmdC6DVcA8HedY3t+YhRK/Ft3ZddmuJvZQST+66BI0AntlZyP1IpApRoXp8c2se3m3swStnmqb0mON1FueYjnUc00FM7MgPPbI8FWM2B14916xYDHaHxH8dq8dd6TFYnBqtWBzkn765NRdDVjv++S3PlahN5FJzL373Tj0eW5GGRXxfkxcYw4PwD/fn4p2rndh9vsVtz7v7fAtKqs342n3zkRId4rbnJZqtDy5NwfJ5sfjB65XoGrz9DeoRqx3f/PNFpMeF4ksbOaaDmNiRHypIjsKiOVF46VSjYk1UDlW0o7FrCI9ztY48ICs+Ao+tSMOLpxpR0+7+ErWJOBwST+26hNgwA762Odcrr0kEODseL0qNxrP7KtA7PLOOgTfrHBjFd/dcxpK0aHyc+59JZYQQeHZnIQZGbPjBgYrbHvsvh2pQ3zmE73+AYzrIiYkd+aVHlqehun0A7zb2KPL6vzl2DSnRIbivIEGR1yf/96V7cxBq0OK5/bf/h99dXj7dhPNNPfjm1jxEheq98ppEgHNv6XM7C9E1OIqfvFk16+d7dl8FBkZt+OFDC1lOTKqUkxCBT63LwCtnruNM/cTN4C639OKFkqv4yLI5HDlDNzCxI7+0fVEyQg1avKxAE5XLLb04cbUL/291Ojcxk8fEhhnwhQ3ZOFJlxtFqs0dfyzIwih++XokV82I5j5EUUZgShU+smov/OdGAi9en1zHwZkerzXj1XDP+tjgTOQkRboyQyL2+sDELyVHBeGrXJVjtjvd8z2Z34Bt/uoiYUAO+yTEddBNedZJfCg/SYcfiZOwpb0HfDId9ztRvyuoRatDi4WVpXn1dCjyfWJ2OtNhQPLfvCmy3/MPvTj84UInBURueZZMJUtDfb86BMTwIT+66CPs0OgaOGxy14Zt/vohMUxg+tyHLAxESuU+oQYenHyxAZVs//vt4/Xu+91/H6nGxuRfffbAA0aEc00F/wcSO/NYjd6dhxOpw64b7O+noH8GeCy340F1zWK5GHhek0+KJLbmobh/AK2eue+Q1Tl3rwh/PXsen1mUgmyscpKDIYD2eeiAP5dd78eIMqjGeP1iN5p5h/OChhQjScT8Sqd/m/ARszI3HTw9Wo7V3GADQ2DmEnxyswr15Cdi6IFHhCEltmNiR31o4Jwp5SZF46aT3mqj8/kQjxuwOjjggr7m/MBHL58bi+YNV6Hfz6rTV7sBTuy4iJToEX9jIFQ5S3oOLkrEmKw4/er0S5v6pj/u40NSD/zp2DY+tSMPdc2M9GCGR+wgh8J0HC2CXEs/svQIpJb756kXoNBo8s7OAFRT0PkzsyG8JIfDo8lRcae3DxeaZ78mYqhGrHb8/2YCNufGYZwzz+OsRAc73+VPb8mAZGMMvj9S59bl/U3YN1e0DeHp7PkINOrc+N9FMCCHwvR2FGLHa8f0pNg6y2h34+p/KYYoIwte3sKMr+ZbU2FB8fkM29l9sw9f+WI6yWgu+viUXSVEc00Hvx8SO/NqOJSkI1mvw0qmpDfqcjdcutMAyMIbH13K1jrxr4ZxofHBJCn5ddg1NXUNuec7mnmH881s1uDcvHpsLWO5D6pFpCsdnijLx53PNeKeu847Hv1ByFZVt/fjejkJEBrNEnnzPp9bNQ4YpDH88ex3L0mPw2HLu4aeJMbEjvxYZrMcDC5Lx2vlmDI7aPPY6Ukr8puwa5idEYHVmnMdeh2gyX7t/PjQC+OHrlW55vu/tuQwJiae3F7jl+Yjc6e82ZCE1NgTf2n0JY7bJGwddswziXw7VYEthIu7jDQryUUE6LX740EIUJEfiBw8tgIZjOmgSTOzI7z26IhWDY3bsueC5JirvXO1EZVs/Hl87lzXvpIikqBB8uigTe8tbcbahe1bP9XZlO9643I7Pb8hGamyomyIkcp9gvRbffbAAtR0D+M+yqxMeI6XEE38uR5BOg+8+yBsU5NvunhuLfV9Yh6x4NrGiyTGxI7+3NC0G2fHheOm058oxf1NWj9gwA3Ys5owvUs5nijIQHxF0Y5P9TAyP2fHt3ZeRaQrD36zLcHOERO6zITcB9xUk4GeHanC9+/0lyK+cacKJq1345tY8xEcGKxAhEZF33TGxE0JECSEOCCEOCiFeFUJMOjBDCJEghDjn3hCJZkcIgUeWp+FCUw+utPS5/fnrLYM4VNmOj61IQ7CeLbRJOWFBOnz1vvk439SDPeWtM3qOXxyuxfXuYTyzsxAGHe/9kbp9e3sBBAS+89qV93y9o28Ez+2rwIp5sXh4WapC0REReddU/tV+DMDzUspNANoA3H+bY/8JANv0kOp8cEkKDDoNXj49/dlHd/Lb4/XQaQQ+tjLd7c9NNF0fWjoHBcmR+OGBSoxY7dN6bJ15AP9eUocPLEnB6kyjhyIkcp+U6BB86d5svFXRjoNX2m98/Tt7LmPE5sD3P8j9SEQUOO6Y2EkpfymlPOj6owlAx0THCSE2ABiEM/kjUpWYMAO2FCbi1XPNGB6b3sXu7fQOW/HKmSZsX5jMUh9SBY1G4MkH8tDcM4xfl12b8uOklPjWrksI1mvxza15HoyQyL0eXzsPOQnh+M5rlzE0ZsObl9uw/2IbvrgxGxmmcKXDIyLyminX2QghVgGIkVKemOB7BgDfBvCN2zz+00KIM0KIM2azeUbBEs3GI3enoX/Ehv0XZ1aiNpH/O9OEoTE7RxyQqqzONGJTfgJ+ebh2ykOcX7vQguN1nfiH++bDFBHk4QiJ3Eev1eDZnQvQ3DOMHxyoxLd3X0ZuYgQ+XcQ9okQUWKaU2AkhYgH8HMDjkxzyDQC/kFL2TPYcUsoXpJTLpJTLTCbTtAMlmq2VGbGYZwzDS6fcU45pszvwX8fqsXxeLApTotzynETu8sSWXIzaHHj+YPUdj+0bseLZfRVYOCcKj65gSTH5nuXzYvHQ0jn43TsNaO8fwQ8eWgi9lntEiSiwTKV5igHAKwCekFI2THLYvQA+J4Q4AmCxEOI/3RcikXsIIfDI3ak409CNmvb+WT/fwSvtaO4ZxuNruFpH6pNhCscnVs3FH043orLt9k2Dnn+zGpaBUTy7sxBa7kciH/XNrblIigrG3xZnYnFqtNLhEBF53VRuZ30SwF0AnhRCHBFCPC2EePbmA6SURVLKe6SU9wA4L6X8lAdiJZq1h+6aA71W4GU3jD74zbFrSI0Nwab8BDdERuR+X9iYhYhgPZ7dWzHp+INLzb343Tv1+NiKdCycE+3dAIncKC48CKX/sB7/cH+u0qEQESliKs1TfiWljBlP3KSU35VSPnWb4+9xa4REbmQMD8Lm/ET86d3r0+4YeLPy6z04Xd+Nv1o9jyscpFrRoQZ8cWM2ymotOFL1/r3NdofEk69eRGxYEL5633wFIiRyLx3LL4kogPETkALOI8tT0TNkxRuXZ97A9Tdl1xAepMNHls1xY2RE7vfxVenIMIbh2X1XYLU73vO9l0414sL1Xjz1QB6iQvQKRUhERETuwMSOAs6aTCNSY0Pw8qmZlWO2941gb3krPrxsDiKCeTFM6qbXavDE1jzUmQff0zjI3D+KH71eiVUZcdixOFnBCImIiMgdmNhRwNFoBB65Ow3vXO3ENcvgtB//P+80wC4l/mr1XPcHR+QB9+bFY1VGHH56sBq9w1YAwPcPVGDYasczOwsgBMuJiYiIfB0TOwpIH75rDrQagZdPT2/0wYjVjt+fbMCmvASkx4V5KDoi9xJC4KlteegZtuIXh2tx4mon/vxuM/5mXQay4iOUDo+IiIjcgIkdBaT4yGBsyI3Hn85ex5jNcecHuLx6rhndQ1YOJCefU5AchQ/fNQf/dewavv6ncqREh+DzG7KVDouIiIjchIkdBaxHl6fBMjCGtyrap3S8lBK/KbuG/KRIrJgX6+HoiNzvK5vnQ6/VoKFzCN99sAAhBq3SIREREZGbMLGjgFWUY0JyVPB7GkrcTlmtBTUdA3h87TzuSSKflBAZjB88tBBf2JiNezl/kYiIyK/olA6ASClajcCHl6XiZ2/XoKlrCKmxobc9/jdl12AMD8L2RUleipDI/R5cxA6YRERE/ogrdhTQPnJ3KgSAP5y+/eiD2o4BHK4y4+Mr0xGkY/kaEREREakLEzsKaCnRISjOMeH/zjbBZp+8icpvj1+DQavBYyvTvBgdEREREdHUMLGjgPfI8jS0943icJV5wu/3DI3hT2ebsWNxMozhQV6OjoiIiIjozpjYUcDbkBuP+IigSZuovHy6CcNWO0ccEBEREZFqMbGjgKfXavDhZXNwpKoDLT3D7/me1e7Afx+vx+rMOOQlRSoUIRERERHR7TGxIwLw8LI0OCTwypn3NlF5/VIbWntH8PgartYRERERkXoxsSMCkBYXinXZRrxyugl2h7zx9d8cu4a5caHYkBuvYHRERERERLfHxI7I5ZG709DSO4KSGmcTlXcbu3GusQd/vWYeNBoOJCciIiIi9WJiR+SyKT8BcWEGvHTS2UTlN2XXEBGsw4fumqNwZEREREREt8fEjsjFoNPgQ3fNwaHKDlxo6sGBS2145O5UhAXplA6NiIiIiOi2mNgR3eThu1Nhd0j8ze/OQEqJT6yaq3RIRERERER3xMSO6CYZpnCsmBeLjv5R3F+YiNTYUKVDIiIiIiK6IyZ2RLf4xKq5EAL45NoMpUMhIiIiIpoSbh4iusUDC5OwbO5GJEQGKx0KEREREdGUcMWOaAJM6oiIiIjIlzCxIyIiIiIi8nFM7IiIiIiIiHwcEzsiIiIiIiIfx8SOiIiIiIjIxzGxIyIiIiIi8nF3HHcghIgC8LLr2AEAD0spx6Z7DBEREREREXnGVFbsHgPwvJRyE4A2APfP8BgiIiIiIiLygDuu2Ekpf3nTH00AOmZyDBEREREREXnGlPfYCSFWAYiRUp6YyTFCiE8LIc4IIc6YzeaZRUtERERERETvM6XETggRC+DnAB6f6TFSyheklMuklMtMJtNMYiUiIiIiIqIJCCnl7Q8QwgBgP4AfSikPzvSYW443A2iYfrgeZwRgUToIui2eI/XjOVI/niP14zlSP54j9eM5Uj9/O0fT/XnSpZRuW/GaSmL3twD+EcAF15cOA9BLKZ+6zTG/klL+wV1BeosQ4oyUcpnScdDkeI7Uj+dI/XiO1I/nSP14jtSP50j9/O0cKf3zTKV5yq8A/Gq2xxAREREREZFncEA5ERERERGRj2Ni914vKB0A3RHPkfrxHKkfz5H68RypH8+R+vEcqZ+/nSNFf5477rEjIiIiIiIideOKHRERERERkY9jYkdERLMmhMgQQmwQQgQpHQsREVEg8qnETggRJYQ4IIQ4KIR4VQhhEEL8WghxXAhx8/iFBCFE6QSPLxRCvHmb59cLIfa6nu9x19eWCiHecn3tK9N5rOvreUKI3TP/qX2Lr50jIUSKEOK6EOKI65fbZomolQ+eoyk91p+o+Ry5jn3P55oQYjOcnZE3wTnT1O/54Dn695s+5+qFEB+d2U/uG9R8foQQaa7z8LYQ4gUhhHB9ndcLKj5HgtcLvnCO7vhYT/9MrmNu/fyNFkKUCCGOCSG23OZxEx4nhCgWQvzH7V5znE8ldgAeA/C8lHITgDYAjwDQSilXA0gWQmQLIWIA/DeAsJsf6PrgfB6A4TbP/3kAZ1zPt00IEQHg5wD+GsAaAA8JIeZN9bFCiEwAPwYQNcOf1xf51DkCsALAc1LKe1y/zDP8uX2Jr52jqT7Wn6j2HE3yuZYD4CNSyicARInAWLXzqXMkpfyMlPIeABsAVAN4bfo/sk9R7fkB8BkAfyul3AAgFcACXi+o/xyB1wu+cI6m8liP/kyT/F3+HoDfACgC8AXX80zkfccJIVYCeBqAfrLXvJlPJXZSyl9KKQ+6/mgC8DEAr7j+/DaAtQDsAB4G0HfLw/8azuHqt3PPTc93HMAyALFSyibp7DLTCSByGo/tB/DQHV7Tr/jgOVoJ4LNCiHeEED+9w2v7BR88R1N9rN9Q+Tl63+ealPJfAYwJIR4FcE1KOXqH1/d5vnaObvIQgP1SysE7vL5PU/P5kVI+KaWscP0xDoAFvF7whXPE6wX1n6M7PtYLP9NEf5eLAPxRSmkHUAdg7iSPnei4JgCfusNr3nDHAeVqJIRYBSAGQD2AZteX+wBkSSn7XMfcfHwcnCfuPtcvuJZIb86mX4QzM7/5+RIAHBNC/B2ALjj/B5dP9bFSysO3xhIofOUcATgA4BkpZb8QYp8QYqGUsnyWP75P8KFz9L7Hzubn9iVqPEdSyhdufV2XBAAfAtA4wx/XJ/nYOQKcFwgfnsnP6otUfn4eBnBZStly0+vP9kf2Ob5yjoQQvF5Q/zma8vWCp36mST5/bVLKgZteI1EI8V+3hPT8BMclSClPCCHmTvZz3MrnEjshRCycS60PAfh7ACGub4Vj8hXIHwB4QkppHf8fLaXcMcFzP+B6vl7X8w3AudS7Hs7l0R+67gJM9bEBycfO0fGbVhcqAWQjABIHHztHEz3W76n1HE1GSlkP4INCiFIhRKKUsm2qj/VVvnaOhBC5ANrGL1r8nZrPjxAiA8BXAdw7k5/NX/jYOeL1gvrP0ZSuFzz5M03CftPvwwEI6SyNvzWuJ285btqVlT5ViimEMMC5XPqElLIBwFk4l0wBYBGcWfdEigH8UAhxBMBiIcSzkxz3vudzLYdWub72+9uEN9VY/JoPnqM3hBBJQohQOO/AXLrN4/2Cr52jaTzWb6j8HE0U724hRJYQQgMgGIBfl/kBvneOXB4G8OoMHudz1Hx+hHP/zksAHpdS9k7pB/JDPniOeL2g8nM0lcd64WeayGUhxDLX7xcCaJjlcZOTUvrMLwB/C6AbwBHXr/8H4AKcy5cVAKJuOvbIJM8x4ddd30sHcBnAvwA4DedmSsC5gXLdHWKb8LF3ek1/++Vr5wjOOzuVcN51+zul///xHM38sf70S83naKLnB3A3gFMAjgH4pNL//3iOJn5+AGUA4pT+fxfo5wfADwG03hRb8VRe099++do5Aq8XVH+OpvJYT/9MEx0D57+RFwC8AGDvbR4z4XFwlpX+dirnTLge4LNcGfsmACXSDaU/QohkODP3N+Q076TN5rH+jOdI/XiO1E9N54gmxnOkbjw/6sdzpH7+eI7c/TNN8hpZABYD2CNv02BsqsdN+nhfT+yIiIiIiIgCnU/tsSMiIiIiIqL3Y2JHRERERETk45jYERERERER+TgmdkRERERERD6OiR0REREREZGP+/8BvZNZK24VTQEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#预测结果可视化一下\n",
    "plt.figure(figsize=(15,5))\n",
    "plt.title('puchase预测')\n",
    "plt.plot(purchase_pred)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(15,5))\n",
    "plt.title('puchase预测')\n",
    "plt.plot(redeem_pred)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.5结果输出与提交"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>purchase</th>\n",
       "      <th>redeem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>3.310539e+08</td>\n",
       "      <td>3.169090e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-09-02</td>\n",
       "      <td>3.318762e+08</td>\n",
       "      <td>3.372455e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-09-03</td>\n",
       "      <td>3.338910e+08</td>\n",
       "      <td>3.632442e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-09-04</td>\n",
       "      <td>2.983191e+08</td>\n",
       "      <td>3.074694e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-09-05</td>\n",
       "      <td>2.407509e+08</td>\n",
       "      <td>2.628057e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2014-09-06</td>\n",
       "      <td>2.266140e+08</td>\n",
       "      <td>2.258706e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>2.435554e+08</td>\n",
       "      <td>2.592158e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2014-09-08</td>\n",
       "      <td>2.970865e+08</td>\n",
       "      <td>3.115468e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2014-09-09</td>\n",
       "      <td>3.321274e+08</td>\n",
       "      <td>3.477437e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2014-09-10</td>\n",
       "      <td>3.265197e+08</td>\n",
       "      <td>3.562431e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2014-09-11</td>\n",
       "      <td>2.916841e+08</td>\n",
       "      <td>3.092719e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2014-09-12</td>\n",
       "      <td>2.392702e+08</td>\n",
       "      <td>2.598512e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2014-09-13</td>\n",
       "      <td>2.253550e+08</td>\n",
       "      <td>2.339112e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2014-09-14</td>\n",
       "      <td>2.475289e+08</td>\n",
       "      <td>2.578186e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2014-09-15</td>\n",
       "      <td>2.950936e+08</td>\n",
       "      <td>3.125493e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2014-09-16</td>\n",
       "      <td>3.345010e+08</td>\n",
       "      <td>3.537239e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>3.280818e+08</td>\n",
       "      <td>3.573622e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>2.927099e+08</td>\n",
       "      <td>3.146179e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>2.448967e+08</td>\n",
       "      <td>2.626592e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>2.275711e+08</td>\n",
       "      <td>2.387440e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>2.530230e+08</td>\n",
       "      <td>2.616172e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2.980719e+08</td>\n",
       "      <td>3.157165e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>3.366748e+08</td>\n",
       "      <td>3.588117e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2014-09-24</td>\n",
       "      <td>3.321948e+08</td>\n",
       "      <td>3.611535e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2014-09-25</td>\n",
       "      <td>2.947106e+08</td>\n",
       "      <td>3.197931e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2014-09-26</td>\n",
       "      <td>2.505384e+08</td>\n",
       "      <td>2.672031e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>2.318269e+08</td>\n",
       "      <td>2.432839e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2014-09-28</td>\n",
       "      <td>2.574471e+08</td>\n",
       "      <td>2.661170e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>3.025702e+08</td>\n",
       "      <td>3.197114e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>3.387019e+08</td>\n",
       "      <td>3.635485e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date      purchase        redeem\n",
       "0  2014-09-01  3.310539e+08  3.169090e+08\n",
       "1  2014-09-02  3.318762e+08  3.372455e+08\n",
       "2  2014-09-03  3.338910e+08  3.632442e+08\n",
       "3  2014-09-04  2.983191e+08  3.074694e+08\n",
       "4  2014-09-05  2.407509e+08  2.628057e+08\n",
       "5  2014-09-06  2.266140e+08  2.258706e+08\n",
       "6  2014-09-07  2.435554e+08  2.592158e+08\n",
       "7  2014-09-08  2.970865e+08  3.115468e+08\n",
       "8  2014-09-09  3.321274e+08  3.477437e+08\n",
       "9  2014-09-10  3.265197e+08  3.562431e+08\n",
       "10 2014-09-11  2.916841e+08  3.092719e+08\n",
       "11 2014-09-12  2.392702e+08  2.598512e+08\n",
       "12 2014-09-13  2.253550e+08  2.339112e+08\n",
       "13 2014-09-14  2.475289e+08  2.578186e+08\n",
       "14 2014-09-15  2.950936e+08  3.125493e+08\n",
       "15 2014-09-16  3.345010e+08  3.537239e+08\n",
       "16 2014-09-17  3.280818e+08  3.573622e+08\n",
       "17 2014-09-18  2.927099e+08  3.146179e+08\n",
       "18 2014-09-19  2.448967e+08  2.626592e+08\n",
       "19 2014-09-20  2.275711e+08  2.387440e+08\n",
       "20 2014-09-21  2.530230e+08  2.616172e+08\n",
       "21 2014-09-22  2.980719e+08  3.157165e+08\n",
       "22 2014-09-23  3.366748e+08  3.588117e+08\n",
       "23 2014-09-24  3.321948e+08  3.611535e+08\n",
       "24 2014-09-25  2.947106e+08  3.197931e+08\n",
       "25 2014-09-26  2.505384e+08  2.672031e+08\n",
       "26 2014-09-27  2.318269e+08  2.432839e+08\n",
       "27 2014-09-28  2.574471e+08  2.661170e+08\n",
       "28 2014-09-29  3.025702e+08  3.197114e+08\n",
       "29 2014-09-30  3.387019e+08  3.635485e+08"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#结果合并一下\n",
    "result=pd.DataFrame()\n",
    "result['date']=purchase_pred.index\n",
    "result['purchase']=purchase_pred.values\n",
    "result['redeem']=redeem_pred.values\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>purchase</th>\n",
       "      <th>redeem</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20140901</td>\n",
       "      <td>3.310539e+08</td>\n",
       "      <td>3.169090e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20140902</td>\n",
       "      <td>3.318762e+08</td>\n",
       "      <td>3.372455e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20140903</td>\n",
       "      <td>3.338910e+08</td>\n",
       "      <td>3.632442e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20140904</td>\n",
       "      <td>2.983191e+08</td>\n",
       "      <td>3.074694e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20140905</td>\n",
       "      <td>2.407509e+08</td>\n",
       "      <td>2.628057e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20140906</td>\n",
       "      <td>2.266140e+08</td>\n",
       "      <td>2.258706e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>20140907</td>\n",
       "      <td>2.435554e+08</td>\n",
       "      <td>2.592158e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>20140908</td>\n",
       "      <td>2.970865e+08</td>\n",
       "      <td>3.115468e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>20140909</td>\n",
       "      <td>3.321274e+08</td>\n",
       "      <td>3.477437e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>20140910</td>\n",
       "      <td>3.265197e+08</td>\n",
       "      <td>3.562431e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>20140911</td>\n",
       "      <td>2.916841e+08</td>\n",
       "      <td>3.092719e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>20140912</td>\n",
       "      <td>2.392702e+08</td>\n",
       "      <td>2.598512e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>20140913</td>\n",
       "      <td>2.253550e+08</td>\n",
       "      <td>2.339112e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>20140914</td>\n",
       "      <td>2.475289e+08</td>\n",
       "      <td>2.578186e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>20140915</td>\n",
       "      <td>2.950936e+08</td>\n",
       "      <td>3.125493e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>20140916</td>\n",
       "      <td>3.345010e+08</td>\n",
       "      <td>3.537239e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>20140917</td>\n",
       "      <td>3.280818e+08</td>\n",
       "      <td>3.573622e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>20140918</td>\n",
       "      <td>2.927099e+08</td>\n",
       "      <td>3.146179e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20140919</td>\n",
       "      <td>2.448967e+08</td>\n",
       "      <td>2.626592e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20140920</td>\n",
       "      <td>2.275711e+08</td>\n",
       "      <td>2.387440e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20140921</td>\n",
       "      <td>2.530230e+08</td>\n",
       "      <td>2.616172e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>20140922</td>\n",
       "      <td>2.980719e+08</td>\n",
       "      <td>3.157165e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>20140923</td>\n",
       "      <td>3.366748e+08</td>\n",
       "      <td>3.588117e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>20140924</td>\n",
       "      <td>3.321948e+08</td>\n",
       "      <td>3.611535e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>20140925</td>\n",
       "      <td>2.947106e+08</td>\n",
       "      <td>3.197931e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>20140926</td>\n",
       "      <td>2.505384e+08</td>\n",
       "      <td>2.672031e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>20140927</td>\n",
       "      <td>2.318269e+08</td>\n",
       "      <td>2.432839e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>20140928</td>\n",
       "      <td>2.574471e+08</td>\n",
       "      <td>2.661170e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>20140929</td>\n",
       "      <td>3.025702e+08</td>\n",
       "      <td>3.197114e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>20140930</td>\n",
       "      <td>3.387019e+08</td>\n",
       "      <td>3.635485e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date      purchase        redeem\n",
       "0   20140901  3.310539e+08  3.169090e+08\n",
       "1   20140902  3.318762e+08  3.372455e+08\n",
       "2   20140903  3.338910e+08  3.632442e+08\n",
       "3   20140904  2.983191e+08  3.074694e+08\n",
       "4   20140905  2.407509e+08  2.628057e+08\n",
       "5   20140906  2.266140e+08  2.258706e+08\n",
       "6   20140907  2.435554e+08  2.592158e+08\n",
       "7   20140908  2.970865e+08  3.115468e+08\n",
       "8   20140909  3.321274e+08  3.477437e+08\n",
       "9   20140910  3.265197e+08  3.562431e+08\n",
       "10  20140911  2.916841e+08  3.092719e+08\n",
       "11  20140912  2.392702e+08  2.598512e+08\n",
       "12  20140913  2.253550e+08  2.339112e+08\n",
       "13  20140914  2.475289e+08  2.578186e+08\n",
       "14  20140915  2.950936e+08  3.125493e+08\n",
       "15  20140916  3.345010e+08  3.537239e+08\n",
       "16  20140917  3.280818e+08  3.573622e+08\n",
       "17  20140918  2.927099e+08  3.146179e+08\n",
       "18  20140919  2.448967e+08  2.626592e+08\n",
       "19  20140920  2.275711e+08  2.387440e+08\n",
       "20  20140921  2.530230e+08  2.616172e+08\n",
       "21  20140922  2.980719e+08  3.157165e+08\n",
       "22  20140923  3.366748e+08  3.588117e+08\n",
       "23  20140924  3.321948e+08  3.611535e+08\n",
       "24  20140925  2.947106e+08  3.197931e+08\n",
       "25  20140926  2.505384e+08  2.672031e+08\n",
       "26  20140927  2.318269e+08  2.432839e+08\n",
       "27  20140928  2.574471e+08  2.661170e+08\n",
       "28  20140929  3.025702e+08  3.197114e+08\n",
       "29  20140930  3.387019e+08  3.635485e+08"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result['date']=result['date'].apply(lambda x:str(x).replace('-','')[0:8])\n",
    "result#这样做 后面的0000000都显示出来了  不需要  所以只需要前8位"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "#输出结果\n",
    "result.to_csv('n_ARIMA.csv',header=None,index=False)"
   ]
  }
 ],
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